**1. Background**

Gut microbiota is defined as the total number of living microorganisms (bacteria, fungi, archaea, viruses and others) present in the intestine. The gu<sup>t</sup> microbiome is a taxonomic characterization of microbial diversity including the set of genomes and, via genes, their physicochemical capabilities [1,2]. In healthy individuals, the gu<sup>t</sup> bacterial microbiota is composed of more than 10<sup>18</sup> di fferent microorganisms. The vast majority of these are bacteria, with some 1100 more prevalent species; of these an estimated 160 species of bacteria are specific to each individual [3].

The microbiome, therefore, is a highly complex structure, involving thousands of microorganisms belonging to very di fferent taxonomic classifications and, consequently, millions of associations between them, making its study a grea<sup>t</sup> challenge [4]. Through advances in bioinformatics, in 2003 the human genome was decoded, a milestone in science. Since then, much attention has been focused on deciphering this extensive network of microbes, the microbiota, also known as the second human genome, or as another organ. These microbes coexist with us and have a larger total number of genes than the human genome. In short, there is no simple description of these structures. However, due to their importance, considerable interest has been generated in the identification of patterns associated with human health and disease states which may even lead to the development of microbiota-based diagnostics and therapies as well as having implications for nutritional or pharmaceutical interventions [2]. To this end, reproducible patterns of gu<sup>t</sup> microbiome variation have been observed in healthy adults, determining the existence of three major microbiota communities, based on the predominance or absence of species of the key genera [5]. Any other combination of key genera or genera not described by Arumugam et al. [5], together with a reduction in biodiversity, is considered dysbiosis [6,7]. Numerous technologies have been applied with the aim of examining the gu<sup>t</sup> microbiota, which has resulted in the capacity and cost of microbiota research being significantly reduced in recent years, mainly due to advances in massive sequencing technologies such as next-generation sequencing. These techniques allow information of interest to be obtained quickly and e fficiently by sequencing regions of the prokaryotic 16S ribosomal RNA gene [8].

In inflammatory bowel disease (IBD), the role of the microbiota in disease development and onset is very clear. While it is true that to date no specific pathogen has been conclusively identified as a trigger, we do know that, for the disease to develop, dysbiosis or a definitive change in the intestinal microbiota must occur and is likely to be the defining event in the development of Crohn's disease (CD). In IBD, it has been documented that the gu<sup>t</sup> microbiota bacterial composition transitions from saprophytic to predominantly pathogenic [9]. Indeed, there is evidence of a significant increase in *Escherichia coli* concentrations, including pathogenic variants, in CD patients with ileal involvement [10]. It unknown at present whether dysbiosis is a cause or a consequence of the development of CD. It appears that the combination of a genetic predisposition and an alteration in gu<sup>t</sup> microbiota are the final triggers of a chronic IBD-type inflammatory process. Specifically, we know that the disease develops in genetically susceptible individuals through dysregulation of homeostasis between commensal microbiota and/or other environmental elements and an altered immune response in the patient. An error in the interpretation of the stimulus or in the regulation of the immune response leads to an imbalance between pro- and anti-inflammatory factors, perpetuating the inflammatory process [11].

The gu<sup>t</sup> microbiota play a crucial role in the development of the immune system and maintenance of the intestinal epithelial barrier. Inflamed ileal mucosa in CD patients shows increased production of tumor necrosis factorα (TNF α), compared to normal ileum, induced by a dysbiosis in the gu<sup>t</sup> microbiota, with a significant increase in bacteria that stimulate TNF production. Numerous bacteria in the commensal microbiota inhibit the release of TNF and other pro-inflammatory cytokines, e.g., bacteria that produce short-chain fatty acids (SCFA), inducing a potent anti-inflammatory e ffect in the intestinal mucosa. In contrast, other types of bacteria, such as *Escherichia coli ECOR-26*, which have been linked to CD, induce increased TNF release and stimulation of IL-10 release [12]. Current hypotheses in favor of a higher release of TNF α induced by intestinal dysbiosis support the idea that restoration of a less pathogenic microbe in the intestinal mucosa (inducing a reduced release of TNF and other pro-inflammatory cytokines) could lead to better disease control [13].

Today, anti-TNF therapy is one of the therapeutic pillars in the managemen<sup>t</sup> of CD, but these drugs only treat the consequences of the disease and not the possible cause. Approximately one quarter of CD patients will be primary non-responders to anti-TNF agents, and one third of responders will experience a loss of response over time [14]. To improve treatment effectiveness, it is essential to study why these patients do not have an optimal response.

Traditionally, the prognosis and monitoring of treatments in patients with CD have been limited to the control of clinical symptoms (e.g., through the Harvey-Bradshaw Index [HBI]: see Table 1) accompanied by imaging techniques (primarily endoscopy and magnetic resonance imaging). However, these tools for assessing disease activity have many drawbacks and limitations. Among them, clinical scoring systems are highly subjective and can be misleading in this disease, characterized by alternating periods of exacerbation and remission [15,16]. Ileo-colonoscopy with biopsies is the current gold standard for the diagnosis and evaluation of inflammatory activity, with the grea<sup>t</sup> disadvantage that it is an invasive procedure [17] and that it is not always possible to reach the diseased area. In an attempt to identify non-invasive markers, fecal calprotectin (FC), a protein originating from the migration of neutrophils to the intestinal mucosa, was introduced as an indirect trait of intestinal inflammation, allowing more objective monitoring than clinical indices, although with low specificity and low positive predictive value depending on the chosen cut-off point [18,19].


Remission ≤ 4 points; mild disease 5–6 points; moderate disease 6–12 points; severe disease > 12 points.

Currently, the role of bacterial gu<sup>t</sup> microbiota is described as a key factor in the development of CD. Various authors defend the reduction in biodiversity and abundance of the phyla *Bacteroidet*es and *Firmicutes* such as *Faecalibacterium prausnitzii* (SCFA-producing bacteria), as well as an increase in the phylum *Proteobacteria* such as *Escherichia coli*, characteristic of patients with this disease compared to healthy individuals [6,7,20]; a decrease in abundance of this species has even been observed after anti-TNF treatment [20]. In this line, one study has identified certain specific microbial profiles that correlate with the recurrence of disease after achieving remission with infliximab treatment [14]. Several studies have also shown that the greater abundance of SCFA-producing bacteria predicted the effectiveness of infliximab [21,22] and another study associated the greater abundance of SCFA with a sustained response to this treatment [23].

A greater understanding of the composition of the bacterial gu<sup>t</sup> microbiota in CD patients, such as the persistence of a significant proportion of certain pathogenic bacteria or low bacterial biodiversity, would make it possible to determine the role of gu<sup>t</sup> microbiota in therapeutic responses and to establish biomarkers of response and relapse, as well as to determine whether it is necessary to restore intestinal normo-biosis in these patients. In addition, different gu<sup>t</sup> microbiota profiles can be found, which enable us to predict the response to different therapeutic lines, thus being more efficient from the outset. Accordingly, this study has been designed to analyze biomarkers of response to anti-TNF treatment in CD through gu<sup>t</sup> microbiota as an alternative non-invasive tool for predicting treatment response.
