Introduction
Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal (GI) tract, which is further divided into ulcerative colitis (UC) and Crohn’s disease (CD).1 IBD is associated with a range of complications that can significantly impact quality of life and health outcomes.2 The predominant symptoms of IBD—such as diarrhea, abdominal pain, gastrointestinal bleeding, weight loss, malnutrition, and fatigue—can lead to substantial psychosocial implications. Other health complications include strictures, fistulas, abscesses, and an increased risk of colorectal cancer,3 particularly in patients with long-standing disease or extensive colonic involvement.3,4 Extraintestinal manifestations, such as arthritis, skin disorders, and liver disease, further contribute to the burden of IBD, underscoring the need for comprehensive management strategies.5
Endoscopy remains the primary method used for diagnosing IBD; however, it is invasive and time-consuming.6 Technologies such as artificial intelligence (AI), endocytoscopy, and molecular imaging have significantly enhanced endoscopic examinations, providing more accurate and detailed insights into IBD detection.7 AI improves risk prediction, genetic data analysis, and disease severity assessment through image analysis.8 Endoscopic molecular imaging offers valuable insights into IBD by assessing disease severity, predicting treatment outcomes, and detecting dysplasia, even in inflamed tissue.9 While endocytoscopy offers extremely detailed, real-time microscopic views of tissue during an endoscopy, magnifying images up to 1,400 times,10 these advances still require non-invasive diagnostic methods.
In IBD, immune system dysregulation drives disease progression through inflammatory mediators that perpetuate local inflammation, alter gut permeability, and result in “gut dysbiosis”.11 Employing gut microbiota and their metabolite biomarkers, which are characteristic of the disease, appears to be a promising non-invasive approach for diagnosis and monitoring. This method can aid in early detection and prediction of IBD, enabling timely interventions and mitigating the risk of complications.12 This highlights the crucial multifunctional role of various biomarkers in IBD. These biomarkers can be utilized in several contexts, including diagnosis, treatment, and determining mucosal healing in IBD patients.13 This review examines the complex interplay between gut dysbiosis, metabolite alterations, and immunological responses in IBD. It seeks to clarify the mechanisms through which alterations in the gut microbiome and its related metabolites lead to the development of IBD, emphasizing particular microbial signatures, metabolomic changes, and immune biomarkers associated with disease activity, progression, and treatment response. Furthermore, it discusses the recently introduced roles of AI and machine learning (ML) in the diagnosis, management, and personalized treatment of IBD. Through this integrative analysis, the article aimed to enhance our understanding of IBD’s multifactorial nature and identify potential avenues for future research and clinical application.
Global burden and prevalence
Over the past few decades, the global burden of IBD has been rising, largely driven by changes in environmental, genetic, and lifestyle factors. Between 1990 and 2019, there was a substantial increase in the global IBD population, rising from 3.3 million to 4.9 million,14 with China and the United States reporting the highest number of cases.15 A 2019 study revealed that the rates of IBD occurrence, deaths, and disability-adjusted life years were higher in older individuals compared to younger ones. Interestingly, men generally experienced higher rates of these indicators than women, until approximately 85 years of age, after which women exhibited higher rates.4 The study found that the highest number of IBD cases occurred in the 50–54 year age group for women and the 60–64 year age group for men. Additionally, the mortality rate associated with IBD was highest among individuals aged 95 years and above.14 Individuals with a family history of IBD, particularly CD, have a significantly increased risk of developing the condition. Siblings of CD patients are 13 to 36 times more likely to develop IBD, while those with a sibling suffering from UC have a seven to seventeen times higher risk. The presence of multiple affected family members further elevates the risk, especially in children. Offspring of two IBD-affected parents face the highest risk, ranging from 33% to 52%.3 A comprehensive analysis of 491 patients demonstrated a dramatic increase in both CD and UC rates over the past century. Incidence rates for CD and UC surged from less than one to over nine and fourteen cases per 100,000 people, respectively, with significantly rising prevalence trends.5 In 2021, a study in Iran analyzed the cost of illness, including medical treatments and other expenses, for IBD and found the annual cost of UC to be $1,077 per patient and CD to be $1,608. Patients over 40 years of age incurred the highest costs, with nationwide totals reaching $8.2 million for UC and $7.1 million for CD.15 A 2022 European study involving 3,687 IBD patients across 12 countries found that disease costs varied based on factors such as disease type, activity, comorbidities, age, gender, country, and healthcare system characteristics.16 UC patients generally had higher costs, particularly for medication.
Factors affecting IBD
The etiology of IBD involves a complex interplay between genetic, environmental, and microbial factors (Fig. 1).17 Among the genetic factors, the human leukocyte antigen (HLA) genes, particularly HLA class II molecules like HLA-DRB1-1502 and HLA-DRB1-1501, are strongly associated with UC, while HLA-DR4 is linked to CD in certain populations. These genes influence the immune response by presenting antigens to T cells, thus playing a critical role in disease susceptibility. Ethnic variability and clinical heterogeneity further contribute to the diverse genetic associations observed in IBD. Polymorphisms in cytokine genes, such as TNFα and LTα in the MHC class III region, regulate immune system activity and are linked to both UC and CD, although results are often inconsistent. The interleukin (IL)-1 receptor antagonist gene allele 2 is associated with increased disease severity in UC and outcomes like pouchitis, highlighting its potential role in modulating inflammation. Family linkage studies also identify genetic predispositions, suggesting linkage disequilibrium near disease susceptibility loci. Other immune-related genes, such as ICAM-1, complement C3, and T-cell receptor genes, show conflicting associations, underscoring the complexity of IBD genetics. These findings collectively illustrate the intricate interplay between genetic predisposition and immune dysregulation in the development of IBD.18 Environmental factors, primarily diet, play a more significant role than genetics in shaping the microbiome; however, specific genotype-microbiome interactions remain important in IBD. For instance, the NOD2 gene variant correlates with an increased abundance of Enterobacteriaceae. A subset of microbiome taxa or functions, such as oxidative stress resistance, might be more directly linked to IBD despite environmental factors driving most microbiome variations.19 Given this complex array of influences, it is crucial to investigate the interplay between these factors for a more detailed understanding of the causes and potential treatments. This review focuses on discussing, in detail, the gut microbiome and metabolome integrated with immune-related biomarkers in IBD.
Microbiome signatures in IBD
The microorganisms, including a variety of bacteria, fungi, and viruses, in the lower part of the GI tract form an enormous and complex ecosystem.20 Apart from changes in the gut bacteriome in patients with IBD, recent studies have reported remarkable changes in the gut mycobiome and virome.20 This implies that non-bacterial microbes, such as fungi and viruses, might also play unique and important roles in IBD pathogenesis and disease activity. Most gut microbes are beneficial and play an immunoprotective role by regulating host immune cells. However, due to disease conditions or imbalances in the host system, alterations in the gut microbiome ecosystem may occur, leading to microbial dysbiosis. Such alterations may contribute to chronic intestinal inflammation and impaired gut barrier function, as seen in IBD. In IBD, there is a shift in the population of microbes, along with the occurrence of inflammation or infection due to contact between microbes and the damaged lining of the intestines.21 Microbial dysbiosis has been demonstrated in both UC and CD of IBD.20
Compared to healthy individuals, the structure of the gut microbiota is significantly altered in IBD at different taxonomic levels.22 The composition of the gut microbiota can change in the early stages of IBD itself.23 Thus, the diversity and composition of the gut microbiota are important factors in the development of the disease. IBD significantly impacts the alpha and beta diversity of the gut microbiome. Alpha diversity refers to the diversity within local communities (habitats), while beta diversity refers to the spatial change in species composition between local communities (habitat).24 Studies have shown that patients with IBD, compared to healthy controls, exhibit reduced alpha diversity.25 This reduction makes the microbiota functionally less capable and less redundant, thereby increasing its vulnerability to perturbations.26
Gut bacteria
More than 99% of the healthy gut bacteriome consists of species belonging to four phyla: Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria.20 In IBD, there is a significant reduction in beneficial bacteria such as Faecalibacterium prausnitzii (F. prausnitzii ) and members of the Ruminococcaceae family,27,28 with exceptions such as Ruminococcus gnavus,29Leuconostocaceae family members,30 and Bifidobacterium species (Table 1).31–54 However, there is an increased presence of pathogenic bacteria, such as Campylobacter concisus, enterotoxigenic Bacteroides fragilis, E. coli, Bacteroides fragilis, Fusobacterium nucleatum, and Mycobacterium avium sub-species paratuberculosis.55
Table 1Table showing organisms of the gut microbiome, their metabolites, and the immune factors they affect
| Microbiome list |
|---|
| Gut bacteria in IBD |
| Bacteria | Abundance | Associated metabolite | Metabolite levels | Effect on immune component | References |
| F. prausnitzii | Decrease | Butyrate | Decrease | Th17/Treg balance disrupted. Blocks IL-6/STAT3/IL-17 pathway and promotes pro- inflammatory effect | 49 |
| Enterobacteriaceae | Increase | LPS | Increase | Reduced IL-10. Increased IL-8, tumor necrosis factor (TNF)-α, and IL-1β | 44 |
| Lactobacilli | Decrease | Indole-3-lactic acid | Decrease | Impairs CD8+ T cells and IL-12a production | 35 |
| | Exopolysaccharides (EPS) | Decreases | Increased pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6). Decreased anti-inflammatory cytokines (IL-10) | |
| | Conjugated linoleic acid | Decrease | Production of colonic IL-6 and TNF-α | |
| Bifidobacteria | Decrease | Indole-3-lactic acid | Decrease | Increased production of IL-8 and TNF-α, and pro- inflammatory cytokines | 34 |
| Flavobacterium | Decrease | Citric acid | Decrease | Production of TNF-α, IL-6, IL-12 and promotion of pro- inflammation | 31,36 |
| | Trimethylamine-N-oxide (TMAO) | Increase | Impacts ATG16L1-induced autophagy. Activates NLRP3 inflammasome. Promotes inflammation | 31,50 |
| Bacteroidetes | Decrease | SCFA | Decrease | Reduced Treg cells | 51 |
| E. coli | Increase | LPS | Increase | Increased IL-8 and other pro- inflammatory cytokines | 33,37 |
| Mycobacterial species | Increase | SCFA | Decreases | Reduced suppression of NF-κB. Reduced activation of inflammasomes. Reduced Treg cells. Reduction in anti- inflammatory mediators (TGF-β and IL-10) | 38,42 |
| Anaerostipes | Decrease | Butyrate | Decreases | Increase in NF-κB-induced pro-inflammatory cytokines TNFα and IL6 | 40,41 |
| Methanobrevibacter | Decrease | Methane | Decreases | Increases IL-6, TNF-α, IL-1β, IFN-γ, NF-κB | 39,43,45 |
| Christensenellaceae | Decrease | Acetate, Butyrate | Decreases | Increase in IL-8, NF-κB activation | 52 |
| Ruminococcus gnavus | Increase | Glucorhamnan polysaccharide | Increases | Increases TNFα | 52 |
| Prevotella copri | Decrease | Valerate and other SCFA | Decreases | Increases TNFα | 48 |
| Clostridium leptum group (IV) | Decrease | Butyrate | Decreases | Reduced Treg differentiation. Reduced IL-22 production. Promotes inflammation through LPS-induced NF-kβ activation. Increased pro- inflammatory factors | 46,47 |
| Gut mycobiome in IBD |
| C. albicans | Increase | SCFA | Decrease | Increases IL-17 and IL-23 production | 12,53 |
| Malassezia | Increase | FFAs such as oleic acid, cell wall carbohydrates, indoles | Increase | Increase production of IL-17 IL-18, IL-8, and IL-6 and Th22 chemokines | 12,53 |
| Kluyveromyces | Decrease | β-glucan | Decreases | Reduction in Treg and IL-10 | 12,54 |
Short-chain fatty acids (SCFAs), produced by members of the gut microbiome, are important for GI tract homeostasis.56 The association between SCFAs and IBD was suggested when changes in associated microbiota, such as Bifidobacterium, were observed to affect SCFA levels.57 In UC patients, a reduction of Bifidobacterium in the colon was observed, which is an important SCFA producer.58,59 SCFAs and gut microbiota in IBD are known to affect reactive oxygen species, whose increased levels can damage the mucosal layer of the GI tract.22 This, in turn, may lead to an increase in intestinal permeability and a leaky gut. Microbes such as Streptococcus, Bifidobacterium, and Lactobacillus, often administered as probiotics, help inhibit reactive oxygen species production and maintain healthy intestinal microbiota.60 It has also been indicated that disturbances in gut microbiota composition and reduced fermentation of dietary fibers in IBD might lead to alterations in SCFAs.23 In a study of IBD patients, reduced tryptophan metabolism was observed, presumed to be due to an altered bacterial gut community.61 Dysbiosis in IBD occurs due to an increase in the taxa Enterobacteriaceae,62 which are facultative anaerobes that use various electron acceptors, such as nitrate, to generate energy. These taxa may also impair gut barrier function through inflammatory cytokine production. Thus, an increase in these taxa leads to alterations in bile acid metabolism and a decrease in tight junctions, resulting in a loss of impermeability in the intestinal epithelium in IBD.63 The beneficial bacterium Lactobacillus is found to be decreased in IBD, and has been shown to have anti-inflammatory effects in mouse models.64 In CD, a lower abundance of F. prausnitzii can signal potential intestinal health issues in adults.65F. prausnitzii plays an essential physiological role and provides mucosal protection and anti-inflammatory functions.65 Gut bacterial signatures have been used as biomarkers, demonstrating their association with mucosal state and related disease symptoms in UC patients.66 Certain bacteria, such as Enterobacteriaceae, Klebsiella, and some Lachnospiraceae species, were found to be more abundant in patients with UC-related symptoms like frequent bowel movements.
Probiotic administration has been shown to cause beneficial changes in the gut microbiota, providing important therapeutic effects for various diseases. For example, rectal infusion of Lactobacillus rectali ATCC 55730 improved mucosal inflammation in pediatric patients with distal active UC and altered the expression levels of several cytokines involved in the processes of IBD.67 Another study found that the administration of Lactobacillus delbrueckii and Lactobacillus fermentum as probiotics decreased inflammatory cytokines, suggesting probiotics could help prevent UC.68 The major anaerobic bacterial species in the colon, Bacteroides, was reduced in UC, but administration of Lactobacilli and Bifidobacteria prior to the induction of experimental UC helped stabilize Bacteroides levels, reducing inflammation and tissue damage.69 A correlation between the composition of gut bacteria and the potential future development of CD was revealed using ML techniques, implying that gut bacteria play a role in the pathogenesis of the illness. Following this approach, a microbiome risk score was created, assigning a risk score to each person based on an examination of their gut bacteria, specifically for healthy first-degree relatives of the cohort.70 These studies demonstrate the potential for using microbial profiles as distinctive markers, and by longitudinally tracking changes in these microbial signatures, researchers could potentially predict disease flares or responses to treatment.
Extracellular vesicles (EVs) in IBD
EVs are tiny spheres enclosed by lipid layers that play a crucial role in the release and transportation of many substances, including carbohydrates, lipids, cell wall components, proteins, DNA, RNA, signaling molecules, etc.71 Intestinal EVs engage in direct or indirect interactions with immune cells, intestinal epithelial cells, and the gut microbiota, actively participating in the regulation of anti-inflammatory responses, restoration of mucosal barrier integrity, and reconstitution of microbiota composition.72 EVs are released from various types of cells, such as intestinal epithelial cells,72 immune cells (macrophages,1 T-cells,72 B-cells, NK cells, polymorphonuclear neutrophils, and dendritic cells), and the microbiota.73 EVs derived from intestinal epithelial cells maintain gut homeostasis and modulate immune responses.72 EVs derived from immune T-cells play a role in intracellular communication and immune modulation. EVs from B-cells are also involved in immune responses. By stimulating macrophages, EVs (containing inflammasomes) can trigger the NF-κB pathway, thus amplifying inflammatory signaling. EVs derived from the microbiota can influence host immune responses and inflammation.74 There are various mechanisms of EV release, which are important to understand further. For example, plasma membrane budding is a mechanism where EVs are released by direct budding of the plasma membrane; however, this requires GTPases and the ESCRT complex.73 EVs can also be released by the fusion of plasma membranes and multivesicular bodies to release exosomes.73 Another mechanism of EV release is the calcium-dependent mechanism, where calcium functions as a second messenger and regulator of EV release.75 EVs are known to facilitate intercellular communication through several signaling pathways by carrying a variety of bioactive molecules such as nucleic acids, proteins, lipids, and metabolites, which in turn initiate intracellular signaling pathways.76,77 These molecules can include tricarboxylic acid (TCA) cycle intermediates, steroid hormones, sterols, enzymes, signaling proteins, surface receptors, mRNAs, microRNAs, sphingolipids, and phospholipids. EVs can also initiate intracellular signaling pathways, which in turn elicit responses in recipient cells.76,77
Recent studies have found that circulating microRNAs (miRNAs) in EVs are small, non-coding RNA molecules that can be used as biomarkers for diseases.78 In the case of IBD, a group of potentially intriguing biomarkers includes miRNAs. Recently, promising findings have been made, such as the identification of elevated expression of circulating miRNAs found in EVs isolated from serum, plasma, or peripheral blood of individuals with IBD.79 An examination of the protein profiles in EVs from individuals with IBD and healthy controls identified certain proteins, including ANXA1 and PSMA7, that are predominantly present in the EVs of IBD patients.80,81 For example, the levels of EV PSMA7 were lower in IBD patients in remission compared to those with active disease, highlighting the potential utility of EV-based biomarkers for monitoring disease progression in IBD. By addressing various aspects—such as release mechanisms, signaling pathways, and the role of EVs as biomarkers in IBD—a comprehensive understanding can be developed of how EVs contribute to the pathophysiology of IBD.
Gut virome
Viruses are increasingly acknowledged as integral constituents of the human microbiome, serving diverse ecological functions, including preying on bacteria, stimulating the immune system, facilitating genetic diversity, enabling horizontal gene transfer, fostering microbial interactions, and enhancing metabolic functions.82 The interaction between bacteria and viruses in the gut highlights the role of viruses in maintaining gut equilibrium and impacting pathological states.83 The virome composition in the healthy human gut includes members of the Malgrandaviricetes (spherical ssDNA) and Caudoviricetes (tailed dsDNA) phage classes.84 Although the bacterial hosts of these viruses remain largely unidentified, Caudoviricetes are presumed to infect a diverse array of bacterial phyla, including Bacteroidetes, Verrucomicrobia, Proteobacteria, Firmicutes, and Actinobacteria.85
Recently, important associations have been observed between the gut virome and IBD. The dysbiosis of the gut virome has been outlined as a condition linked to the pathogenesis of IBD, revealing elevated levels of phages infecting Clostridiales, Alteromonadales, and Clostridium acetobutylicum in individuals with IBD compared to healthy subjects.86 A higher abundance of the Retroviridae family in IBD patients has also been noted in a study on Chinese cohorts involving IBD patients and healthy controls, which identified 139 IBD-associated viral OTUs.87 An increase in eukaryotic virome evenness and richness in IBD patients was observed compared to healthy controls. Further, Genomoviridae and Retroviridae were two eukaryotic viral families found to be enriched in IBD patients. In terms of the prokaryotic virome, there was a significant decrease in virome diversity in IBD patients compared to controls. Families like Siphoviridae and Myoviridae were enriched in patients, while crASS-like and Quimbyviridae were decreased. At the OTU level, numerous IBD-enriched Siphoviridae and Myoviridae viral OTUs were found, which infect bacteria such as Escherichia, Klebsiella, and other opportunistic pathogens that induce inflammation and trigger many diseases. Moreover, fecal virome transplantation in mouse models verified that the colonization of these viruses, characterized in IBD, modulates experimental colitis.87 However, more comprehensive and focused research is required to obtain a detailed understanding of the virome in IBD (Table 2).87–89
Table 2Table listing the changes in the abundance of gut virome in IBD
| Gut virome | Abundance | Role | References |
|---|
| Myoviridae | Increase | These are temperate viruses belonging to the order Caudovirales, but their function in IBD virome remains mostly unclear | 87 |
| Microviridae | Decrease | Belonging to the order Petitivirales, impacts in bacterial dysbiosis | 88 |
| Siphoviridae | Increase | Temperate viruses belonging to the order Caudovirales, impacts in bacterial dysbiosis | 87 |
| Quimbyviridae | Decrease | Role in IBD remains unclear | 87 |
| Genomoviridae | Increase | Belonging to order Geplafuvirales, the role remains unclear | 87 |
| Anelloviridae | Increase | They are useful for reporting of reduced immune surveillance and effectiveness of immunosuppression | 89 |
| Retroviridae | Increase | The overgrowth of this family has been linked to several diseases including CD but its exact role remains unclear | 87 |
Gut mycobiome
Fungi constitute approximately 0.1% of the gut microbiome and have been identified in the GI tract of around 70% of healthy individuals. They interact with viruses and bacteria in the gut, displaying both antagonistic and synergistic relationships.90 The mycobiome of the healthy human GI tract is primarily composed of three major phyla: Basidiomycota, Ascomycota, and Chytridiomycota.90 A dysbiosis observed in the fungal community plays a crucial role in IBD by impacting the composition of the gut microbiota or promoting the generation of pro-inflammatory cytokines.91 A distinctive feature of IBD is an increased ratio of Basidiomycota to Ascomycota (Table 3).92–94 An increase in the abundance of fungi, such as Candida species (which can exacerbate inflammation), and a decrease in Saccharomyces have been observed in IBD cases.96–98 Another report indicated elevated abundances of Sterigmatomyces, Aspergillus, Candida, and Wickerhamomyces, along with lower abundances of Penicillium, Exophiala, Alternaria, Acremonium, Trametes, Epicoccum, and Emericella in patients with UC.99 In a clinical study consisting of colon biopsies from 10 IBD patients and 18 healthy controls, Pseudomonas was elevated, and the opportunistic pathogen Malasseziales was found to be the most abundant in UC. Also, an increased Basidiomycota to Ascomycota ratio was found in UC compared to CD, due to the higher abundance of Malasseziales, which may indicate UC.100 Fungal dysbiosis was found to facilitate IBD by enhancing CD4+ T cells in a mice model and in human colonic and CD4+ T cell samples from healthy donors,101 UC patients, and CD patients. In this report, Candida albicans was found to increase pro-inflammatory cytokine production, and slower progression of IBD was observed when terbinafine was used to deplete fungi.101
Table 3Table listing the changes in the abundance of gut mycobiome in IBD
Abundance
|
|---|
| Increased | Decreased | Reference |
|---|
| C. albicans; Malassezia; Filobasidiaceae; D. hansenii; Xeromyces; Rhodosporium; Lipomyces; Yadazyma; Lipomyces; Yamadazyma friedrichii; Lypomyces doorenjongii | Saccharomyces cerevisae; Saccharomyces boulardii; Kluyveromyces; C. tropicalis; Zygomycota; Aspergillus; Debaromyces; Cladosporium; Microdochium; Phaeosphaeria; A. rubrobrunneus | 92–94 |
Correlating microbial signatures with disease outcome and treatment response
When discussing microbial signatures in IBD, it is important to highlight the specific compositional changes in the gut microbiota associated with disease activity, disease progression, and treatment response. In patients with IBD, the intestinal microbiota is dysregulated compared to healthy individuals, showing decreased bacterial diversity—especially in the abundance of Firmicutes and Bacteroidetes—and an increase in Proteobacteria.102 Similarly, between CD and UC, patients with CD show a higher level of dysregulation, with more reduced diversity and a less stable microbial community, which can be considered a specific signature of CD.103 Microbial biomarkers, such as specific bacterial strains or metabolites, can indicate whether a patient is likely to respond to a particular treatment. For instance, in patients with CD using the anti-integrin therapy Vedolizumab, those who achieved remission were found to have a gut microbiome enriched with Roseburia inulinivorans and a Burkholderiales species compared to non-responders.104 Similarly, a higher absolute abundance of Bifidobacteriales and a lower abundance of Actinomycetales at baseline were associated with a rapid response to infliximab therapy in pediatric IBD patients.33 Additional studies like these will help us understand the microbial signatures associated with IBD and can help design personalized treatment strategies, ultimately improving patient outcomes.
Metabolome signatures in IBD
The metabolome refers to the pool of small metabolites present in a biological sample under specific conditions at a particular time.105 Some important metabolites include lipids, amino acids, or TCA cycle intermediates, among others. A diverse range of biosamples, including easily accessible blood, urine, serum, feces, and saliva, as well as less accessible and more invasive samples such as organs, tissues, or even cells, have been used to identify metabolome markers in IBD.106 These samples provide varying degrees of information; for example, urine provides a thorough overview of both endogenous and exogenous metabolism, stool gives insight into digestive metabolism, blood offers a systemic perspective, tissue samples provide direct insight into localized infection, and less conventional samples like breath may contain information reflecting metabolic dynamics.107
Several studies have reported variations in a variety of metabolites from different types of biosamples in patients with IBD compared to healthy controls. For example, in a large group of 117 individuals with CD, an upregulation of 1-octen-3-ol, 6-methyl-2-heptanone, 2-piperidinone and heptanal was observed in the active CD group compared to healthy controls in fecal samples. However, in patients with CD, reduced quantities of methanethiol, 3-methyl-phenol, short-chain fatty acids, and ester derivatives were observed.108 In another study, metabolites in fecal samples were found to distinguish between UC and CD, as well as between healthy controls and UC.109 In the fecal samples of CD patients, lactate, succinate, alanine, and tyrosine were enriched, while in UC patients, leucine, alanine, and tyrosine were the most abundant metabolites.34 In yet another study, 53.6% of lipid metabolites were significantly altered in CD compared to controls, whereas in UC only five lipid-related metabolites were decreased.110 Both CD and IBD showed a consistent decrease in various fatty acids compared to controls. Interestingly, the amount of glycerol was notably reduced in CD, indicating lipolysis. Also, the essential acylcarnitine metabolites were reduced in CD compared to both UC and control groups. Bile acid pathways were significantly altered in IBD, with increased primary and secondary bile acids in CD, while UC exhibited reduced primary bile acids and altered secondary bile acids. The amounts of TCA cycle intermediates, including citrate, aconitate, α-ketoglutarate, succinate, fumarate, and malate, were significantly decreased in CD. Additionally, β-hydroxybutyrate, derived from the abundance of acetyl-CoA, exhibited the most substantial reduction in CD, being 11 times lower than that in controls and 18 times lower than in UC subjects.110
Metabolic dysfunction is defined as a series of abnormal or disrupted metabolic processes occurring in the body, particularly those related to energy production, nutrient utilization, or the regulation of various molecules. In the case of IBD, this is marked by decreased levels of trimethylamine-N-oxide, reduced SCFAs like butyrate, lower hippurate levels, and alterations in primary and secondary bile acid profiles.107 This dysbiosis can contribute to inflammation by influencing metabolic pathways or the immune system.111 Several metabolites in the gut are contributed by the resident microbiota. Thus, microbial dysbiosis is expected to be associated with metabolic imbalance as well. For example, in IBD, there is an imbalance in microbial composition, particularly an increase in Proteobacteria and a decrease in Firmicutes. Therefore, the roles of specific bacteria, such as Escherichia coli and the butyrate-producing F. prausnitzii, become very important. This suggests that combining microbiome and metabolome explorations may provide valuable insights to understand, diagnose, and treat IBD.112 Towards this, Lijun Ning et al. (2023) found unique biomarkers related to IBD diseases consisting of gut bacteria and metabolites.113 These biomarkers are expected to have a low likelihood of being incorrectly identified in both GI and non-GI-related diseases. This suggests that they could be valuable disease-specific markers for IBD and could have diagnostic potential.113
Metabolomic profiling has proven valuable in predicting treatment responses in IBD patients by identifying specific metabolites associated with therapy outcomes. Key metabolites like bile acids, glycine, linoleic acid, N-acetylserotonin, and methylglutaric acid have been linked to responses to therapies like anti-TNF and infliximab, with distinct profiles emerging between responders and non-responders.114 Particularly, bile acids, along with urinary cysteine and bile acids in various bodily fluids, have been identified as potential indicators of treatment efficacy. Furthermore, fecal lipid profiles show higher predictive accuracy than serum profiles. These findings emphasize the potential of metabolomic analyses, particularly of fecal samples, in enhancing personalized treatment strategies and increasing the understanding of IBD’s metabolic alterations.114
To explore metabolite profiles, it is essential to implement highly sensitive techniques for metabolomics analysis. The two key analytical techniques used in metabolomics are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). NMR provides insights into metabolite structure and concentration by detecting energy changes in nuclei under a magnetic field. It includes 1D-NMR, commonly used in high-throughput studies, and 2D-NMR, which resolves overlapping peaks for complex metabolite characterization using techniques like COSY and TOCSY.115 While NMR faces limitations such as low sensitivity and overlapping proton peaks, it is still expected to remain a vital tool in healthcare for at least the next decade. Its advantages, including minimal sample preparation, high reproducibility, and the ability to analyze an entire sample in a single measurement, make it indispensable despite its limitations.116
MS, on the other hand, measures the mass-to-charge ratio (m/z) of ionized metabolites, offering high sensitivity and specificity. MS is often preceded by chromatographic separation (e.g., LC-MS or GC-MS) to reduce sample complexity and improve accuracy.115 However, structural elucidation in untargeted analyses presents significant challenges, particularly with stability and reproducibility during large-scale sample runs using untargeted LC-MS. These issues underscore the need for advancements that enhance reproducibility and improve the accuracy of structure elucidation.116
In IBD research, untargeted metabolomics is particularly valuable as it captures a holistic metabolic profile without predefined targets. The workflow includes spectral processing to generate metabolic features, data analysis to explore associations with phenotypic traits, biomarker discovery for diagnostics, and pathway analysis to connect metabolites with biological processes. Advanced bioinformatics tools are essential for handling the complexity of metabolomics data, enabling multi-omics integration and the identification of biomarkers and pathways relevant to IBD.117 Together, these techniques provide a comprehensive understanding of disease mechanisms and support the development of personalized therapeutic strategies.
Immunological biomarkers in IBD
The need for precise diagnostic tools and effective treatment strategies for IBD highlights the importance of immunological biomarkers. With intensive research being conducted to identify immunological biomarkers and considering the vast amount of related data being generated, it is now possible to speculate on the dynamics between immunological components and the gut microbiome. Understanding how dysbiosis in the gut microbiome can affect the regulation of various immune system components is crucial to elucidating the mechanisms by which the disease progresses. Numerous studies to date have identified different immunological biomarkers, including various types of T cells, receptors, antibodies, interleukins, and cytokines. These biomarkers can be classified according to their clinical applications: diagnosis, prognosis prediction, and treatment monitoring.
Diagnosis
Immunological biomarkers are essential for the accurate diagnosis of IBD, helping to differentiate it from other gastrointestinal disorders, particularly in cases where clinical symptoms are ambiguous. Specific biomarkers, such as anti-Saccharomyces cerevisiae antibodies and perinuclear anti-neutrophil cytoplasmic antibodies, are commonly used to distinguish between CD and UC, respectively.53,118,119 These markers provide less invasive diagnostic options and complement traditional methods like endoscopy. Elevated levels of pro-inflammatory cytokines, including IL-1β and IL-8, have been identified in IBD patients, aiding in the identification of active inflammation. IL-1β is a biomarker that has been identified due to its elevated levels in the serum of patients suffering from IBD, in patients with relapse, and also in pediatric cases of IBD.34,35 IL-1β by itself is not capable of exacerbating IBD, but the effect is seen through fluctuations in the levels of inflammasomes like NLRP3, an important source of mucosal IL-1β.36 Lower levels of the NLRP3 inflammasome and, consequently, lower levels of IL-1β lead to a decreased state of colitis in mice.120 Furthermore, in mice, aggravated intestinal inflammation is linked to the bacterial members of the genus Prevotella, mainly Prevotella intestinalis, which can cause a reduction in the production of SCFAs, especially acetate.37 Interestingly, it is now established that acetate is involved in the suppression of NLRP3 inflammasome-mediated production of IL-1β.38 From these studies, it may be understood that in extreme cases of intestinal inflammation, Prevotella species cause a downregulation of acetate production, which in turn increases IL-1β production, thus promoting inflammation. Similarly, IL-8 levels are seen to be elevated in the serum of patients with IBD relapse and also in pediatric cases of IBD.34,35 The increase in IL-8 levels in CD and UC can also be explained by the increased levels of various Enterobacteriaceae, like E. coli, and decreased levels of Bifidobacterium and Lactobacillus species in the gut.39–42 A study performed using IBD isolates showed that the flagellin shed by mucosa-associated E. coli induces IL-8 expression through a MAPK-dependent pathway.42Bifidobacterium species are also shown to bind to and neutralize lipopolysaccharides (LPS) from E. coli, which, if not neutralized, can lead to LPS-induced increases in IL-8 levels.33 It is possible that due to the increased levels of E. coli and lower levels of Bifidobacterium species, LPS produced by E. coli is not neutralized, leading to more LPS-induced IL-8 production and causing an increase in IL-8 levels. Bifidobacterium is also an SCFA-producing bacterium, and these SCFAs produce an anti-inflammatory effect by blocking the NF-κB signaling pathway. Thus, low levels of Bifidobacterium in IBD, and in turn lower production of SCFAs, can lead to increased pro-inflammatory consequences.57 Similarly, an experiment performed on IBD patients demonstrated that an increase in Lactobacillus species, and thus an increase in butyric acid produced by them, leads to decreased levels of IL-8 and other pro-inflammatory molecules.43 From this, we can infer that lower levels of Lactobacillus may increase IL-8 levels. Dysbiosis in the gut microbiome, characterized by altered levels of bacterial species such as Prevotella intestinalis and Escherichia coli, further influences the production of these cytokines, contributing to their diagnostic relevance.
Prognosis prediction
Immunological biomarkers are instrumental in predicting the progression of IBD and identifying patients at risk for severe disease or complications. For instance, Oncostatin M (OSM), which belongs to the IL-6 family of cytokines, has been shown to be an important biomarker in IBD.121 It is immediately released during degranulation and is capable of initiating other signaling pathways, such as the JAK-STAT pathway or PI3K-Akt pathway, which aid in the progression of this disease.118,121 The level of mucosal OSM has been found to be upregulated in patients newly diagnosed with IBD and in patients with a relapse, even after surgery.118,121 High levels of OSM have been identified in patients suffering from CD and UC and have also been proven to be responsible for non-responsiveness to anti-TNFα therapy.119 Dysbiosis in the case of CD can result in a decreased abundance of Roseburia intestinalis, a gut microbiome member, and the reduced levels of this species are responsible for the increased levels of OSM in CD patients.122 Interestingly, the normal abundance of R. intestinalis is able to suppress intestinal inflammation by downregulating pro-inflammatory cytokines and increasing anti-inflammatory cytokines and regulatory T cells (Tregs).122 How this species impacts the components of the immune system can be explained by the fact that R. intestinalis is an SCFA-producing bacterium capable of synthesizing butyrate, which has been reported to have multiple effects on immune regulation, one of which includes promoting the proliferation of Tregs.44 From this, it may be understood that in the case of IBD, under dysbiosis, the abundance of R. intestinalis is decreased, which in turn leads to a decrease in butyrate production, thus downregulating Tregs, anti-inflammatory factors, and upregulating pro-inflammatory mediators, including OSM.
Treatment monitoring
Biomarkers also play a critical role in monitoring treatment response and guiding therapeutic decisions in IBD. A recent study performed to identify biomarkers specific to cases of IBD remission or relapse compiled a list of interleukins, cytokines, and other immunological factors, including Galectin-1, IL-15, IL-21, IL-25, IL-13, IFN-β, CXCL11, CXCL9, CXCL10, and G-CSF, whose levels are elevated in patients with a relapse.35 The possibility that higher levels of IL-15 could be due to changes in the levels and composition of the Bacteroidetes and Firmicutes phyla, as well as a change in the abundance of butyrate-producing bacteria, such that the levels of butyrate and other SCFAs are reduced, has already been highlighted.45 The link between lower levels of butyrate and other SCFAs with elevated levels of IL-15 may be speculated to be similar to the case of IL-8 and IL-1β. An experiment performed on patients with hepatocellular carcinoma showed that increased levels of gram-negative bacteria and decreased levels of gram-positive bacteria, like Firmicutes, are linked to increased levels of IL-25.123 The increased levels of IL-25 in IBD may also be due to a similar case of dysbiosis. In IBD, significantly higher levels of the bacteriophage Caudovirales have been observed, and this, combined with a bacterial infection where these phages are replicated through the bacteria, can trigger pro-inflammatory effects, heightened T cell immune responses, and IFN-β production, along with suppression of phagocytosis and TNF production, thus maintaining a state of gut inflammation.123 It is now known that CXCL9, CXCL10, and CXCL11 have strong bactericidal activity, and their increased levels could be due to the higher abundance of E. coli in cases of IBD, resulting in infections by bacteria like Listeria monocytogenes and Bacillus anthracis.46–48
Another study performed on CD and UC patient samples through mass cytometry identified a list of immunological molecules, including CXCR3+ plasmablasts, HLA-DR+CD38+ T cells, and IL1B+ macrophages and monocytes, that were characteristic of IBD samples; elevated IL17A+ CD161+ effector memory T cells, HLA-DR+CD56+ granulocytes, and reduced type 3 innate lymphoid cells specifically in UC samples; and IL1B+ dendritic cells, IL1B+TNF+IFNG+ naïve B cells, IL1B+HLA-DR+CD38+ T cells, and IL1B+ plasmacytoid dendritic cells specifically in CD samples.124 How gut dysbiosis influences the levels of these immune components is not yet fully understood and warrants further exploration. Much remains unknown regarding how changes in the abundance and composition of the gut microbiome lead to higher levels of these biomarkers.
Integration of the gut-microbiome, metabolome, and immunological aspects in IBD
The sections thus far have discussed three kinds of biomarkers—the gut microbiome, the gut metabolome, and immunological biomarkers—independently. However, it is interesting to note the interplay between gut dysbiosis, the alteration in metabolite levels, and the consequent increase in pro-inflammatory factors and reduction of anti-inflammatory factors. As already established, IBD is characterized by gut dysbiosis, which accounts for the first group of biomarkers. This imbalance in the abundance of different gut microbiota implies a corresponding imbalance in the levels of various metabolites associated with them. Broadly, SCFAs and LPS are two common groups of metabolites whose levels decrease and increase, respectively, due to gut dysbiosis, forming the second group of biomarkers. Various cytokine levels are affected by these changes in metabolite levels. The cytokines whose levels change significantly and are identified as the third group of biomarkers include IL-12, IL-10, IL-8, IL-6, IL-1β, and TNF-α. An overall idea of this integrated concept of the three biomarkers is visually represented in Figure 2. This concept can be further understood by examining F. prausnitzii, whose abundance in the gut decreases in IBD. This bacterium is a major butyrate-producing organism, and the decrease in its abundance causes a corresponding decrease in butyrate levels.125 Butyrate, an SCFA, impacts the host immune system, supporting the fact that a reduction in butyrate levels disrupts the Th17/Treg balance. It also blocks the IL-6/STAT3/IL-17 pathway and promotes pro-inflammatory effects, ultimately exacerbating the disease.122 This is just one example of a mechanism that links all three types of biomarkers seen in IBD. Other such mechanisms can be similarly understood from Table 1 and are visually summarized in Figure 3. Considering the interactions mentioned above and those outlined in Table 1, it may be hypothesized that: i) alterations in gut microbiome composition directly or indirectly influence the production of immunological biomarkers in IBD patients, ii) the metabolomic signatures associated with dysbiosis in IBD correlate with specific immunological responses and disease severity, and iii) modulating the gut microbiome may lead to measurable changes in both immunological biomarkers and metabolomic profiles, resulting in improved clinical outcomes for IBD patients.
The interplay between the gut microbiome, metabolome, and immune factors in IBD presents numerous complexities and unresolved questions. One significant uncertainty lies in the causal relationships between specific microorganisms, metabolites, and immune responses. While associations have been established, the directionality of these relationships remains unclear. For instance, it is uncertain whether dysbiosis leads to altered immune responses, or if inflammation modifies microbiome composition. Alterations in metabolite profiles, as discussed above, have been observed in IBD patients, yet the specific metabolic pathways affected and their implications for immune function are not fully elucidated. The role of metabolites produced by gut bacteria in modulating immune responses presents a complex interaction that warrants further investigation. Individual variability in immune responses to microbial and metabolic signals complicates the understanding of pathogenesis. Factors such as genetics, environmental influences, and prior exposures can significantly affect how the immune system interacts with the microbiome. To address these uncertainties, several research methods and technical approaches could be employed. Conducting longitudinal studies that track changes in microbiome composition, metabolomic profiles, and immunological biomarkers over time could help establish causal relationships. This approach would allow researchers to observe how shifts in one domain influence the others. Utilizing an integrative multi-omics approach (combining genomics, transcriptomics, proteomics, and metabolomics) can provide comprehensive insights into the interactions between microorganisms, metabolites, and immune factors. Advanced computational models could analyze this data to identify key pathways involved in IBD pathogenesis. Developing animal models that mimic human IBD can facilitate controlled experiments to test specific hypotheses about microbial influence on immune responses. For example, germ-free mice could be colonized with specific bacterial strains to observe subsequent changes in immune activation and metabolite production. Designing clinical trials that monitor immunological biomarkers alongside microbiome and metabolome changes during treatment could provide insights into how therapies influence these interactions. This could lead to personalized treatment strategies based on individual biomarker profiles. These uncertainties need to be addressed through targeted research methods, enabling scientists to deepen their understanding of IBD’s pathogenesis and potentially uncover new therapeutic targets for managing this complex disease.
AI-ML based advancements
As our understanding of IBD progresses and we strive to enhance clinical trial outcomes and treatment goals, AI and ML have emerged as promising tools to improve diagnostic processes and treatment outcomes. Various ML algorithms have demonstrated their efficacy in predicting patient responses to therapies and assessing disease severity, such as Random Forest and Support Vector Machines.95,126 These algorithms utilize high-dimensional data, ranging from clinical genomics to microbiome data, enabling a better understanding of individual patient profiles. A study proposes the Holistic AI in Medicine framework, which uses multimodal inputs such as tabular data, time-series, text, and images to enhance predictive modeling in healthcare. The integration of multimodal data using AI techniques has been shown to improve diagnostic accuracy.127 However, many challenges remain unresolved in this field. One of the issues is the lack of diversity in patient samples, which can lead to biased predictions. This highlights the need for the development of robust AI models that generalize well across populations. Research has shown that AI models trained predominantly on data from specific demographics can result in imbalances in healthcare outcomes, with less accurate algorithms for underrepresented racial or ethnic groups.128 Moreover, the increasing applications of AI in managing IBD present exciting prospects. AI may not only predict how individuals respond to biological therapies but also contribute to refining the standard of care. This sets the groundwork for personalized treatment in the future, with the potential to reduce costs and improve overall disease management.129 The integration of AI in the treatment and diagnostics of IBD offers significant potential for enhancing patient care through improved and personalized strategies. To recognize and address the challenges, future research must focus on validating AI systems in real clinical environments with diverse data to optimize the models.
Future research directions
Future research in understanding IBD should focus on conducting large-scale longitudinal studies to explore the intricate relationships between immunological biomarkers, the microbiome, and the metabolome.130 These studies should aim to identify a diverse cohort of participants, including those diagnosed with CD and UC, alongside healthy controls for baseline comparisons. Inclusion criteria must consider age diversity and disease duration to evaluate temporal changes in biomarkers effectively, with a target sample size of 500–1,000 participants to ensure robust data analysis.131
The study design should adopt a prospective cohort framework, facilitating data collection at multiple time points, such as baseline, six months, and annually thereafter. Regular follow-ups will be essential for gathering biological samples (blood and feces) and clinical data, including symptom diaries and medication use. An intervention group receiving dietary modifications or probiotics could provide insights into their impact on biomarkers over time (https://training.cochrane.org/handbook ).132
Data collection methods must encompass comprehensive biological sampling for immunological analysis and microbiome sequencing, alongside standardized clinical assessments to evaluate disease activity. Advanced statistical analyses and machine learning approaches will be crucial for identifying patterns that predict disease flares or treatment responses based on microbiome and metabolomic changes.133,134
Ethical considerations are paramount; thus, obtaining informed consent and ethics approval from relevant boards is essential. Finally, the dissemination of findings through publication in peer-reviewed journals and engagement with healthcare providers will enhance awareness of potential biomarkers and their clinical relevance.135 By implementing these structured strategies, researchers can gain valuable insights into the complex dynamics of IBD, ultimately informing future therapeutic strategies and improving patient outcomes.
Conclusions
In this review, we have summarized biomarkers of IBD with a major focus on signatures in the gut microbiome. We discussed the characteristic variation in the levels of different organisms in the gut, how this variation, in turn, causes fluctuations in the levels of metabolites produced by these organisms, and finally, how the imbalance of these metabolites can induce altered levels of various components of the immune system. Thus, this review provides a complete outlook on the microbial, metabolic, and immunological signatures and their interrelations. Although extensive research is being conducted to identify biomarkers for IBD, the ones that have been identified are not ideal. Most biomarkers reported to date are invasive, not specific to IBD, and not highly sensitive. Moreover, the biomarkers reported across different studies are inconsistent due to variations in study protocols, sample sizes, populations, environmental influences, experimental bias, and other factors. This implies that there is no standard panel of biomarkers that can be universally applied across all populations and stages of IBD. The biomarkers known so far need to be validated through longitudinal studies across diverse populations of larger sizes, using various study designs, and in heterogeneous patient samples. This will help establish standard biomarkers that can be used in all IBD cases. These biomarkers can then be used for timely prognosis and accurate diagnosis of IBD and can also inform personalized treatment strategies for patients.
Declarations
Funding
None.
Conflict of interest
The authors have no conflict of interest related to this publication.
Authors’ contributions
Study concept and design (PSP, RK, VS, TP), creating tables and figures (RK, PSP, VS), drafting of the manuscript (PSP, RK, VS), critical revision of the manuscript for important intellectual content (TP), and study supervision (TP). All authors have made significant contributions to this study and have approved the final manuscript.