Severine Vermeire

Background and aims: Despite the importance of eosinophils in histologic scoring systems of ulcerative colitis (UC), the impact of advanced therapies on eosinophils is poorly understood. Additionally, data regarding distinct eosinophil subsets in UC are scarce. Methods: Colonic immune cells from 20 patients were analyzed by flow cytometry, alongside matched stool samples measuring fecal calprotectin and eosinophil-derived neurotoxin. In a separate cohort of 29 UC patients starting advanced therapy, immune cells from blood and colon were profiled at baseline and post-induction. Treatment response was defined as a Mayo endoscopic subscore of 0-1. A retrospective cohort (n = 21) was used to validate our findings. Results: Inflamed colonic tissue was characterized by an increased abundance of total eosinophils (P = .007), with an enrichment of B-Eos (CD80− PD-L1−) and depletion of A-Eos (CD80+ PD-L1+ active eosinophils) (both P < .0001) compared with unaffected tissue (correlated with histological activity RHI, P = .003). Endoscopic response to advanced therapy was associated with a reduction in total eosinophils (P = .0008) and various other immune cells, whereas nonresponse showed significant immune remodeling. Exploratory analyses in patients treated with vedolizumab (n = 11) demonstrated reductions in colonic total eosinophils (P = .07) and B-Eos (P = .008), together with an increase in A-Eos (P = .0003), resulting in an increased A-Eos/B-Eos ratio irrespective of endoscopic outcome. Conclusion: We confirmed enrichment of total eosinophils in inflamed colonic tissue, characterized by an increase in B-Eos and a reduction in A-Eos, resulting in a decreased A-Eos/B-Eos ratio. Exploratory analyses suggest that vedolizumab is associated with reduced B-Eos, increased A-Eos, and restoration of the A-Eos/B-Eos ratio, raising the hypothesis that this therapy may differentially modulate mucosal eosinophil biology. These findings identify distinct eosinophil subsets as potential biomarkers and therapeutic targets in UC and provide a biological framework for future mechanistic studies.

Background and aims: Perianal fistulizing Crohn's disease (pCD) affects 20% of patients with Crohn's disease (CD) and severely impacts quality of life. Current therapies fail to provide sustained relief, and the molecular underpinnings of pCD remain poorly understood. This study aimed to elucidate the molecular landscape of perianal fistulas through multiomic profiling. Methods: Paired fistula-tract and adjacent rectal mucosal biopsies were collected from 63 patients (48 with pCD, 15 with cryptoglandular fistula [CPTGL]). Longitudinal sampling generated 101 unique molecular profiles, comprising of both RNA sequencing (RNA-seq) and 16S rRNA sequencing from both tissue sites, followed by integrative multiomics and gene network analyses. Results: Unsupervised clustering revealed three patient clusters primarily defined by host gene expression, with minimal contribution from microbial profiles. Fistulae in clusters 1 and 2 showed strong immune activation and epithelial-mesenchymal transition (EMT). In contrast, cluster 3 fistulae displayed keratinization and metabolic reprogramming resembling psoriatic skin, together with reduced JAK-STAT signalling. Cluster 3 was enriched for patients classified as TOpClass:2a, who are more suitable for surgical repair (p = 0.02). Conversely, cluster 2, characterized by rectal keratinization and EMT in both fistula and rectum, showed the highest MRI inflammatory-mass score (p = 0.02) and a greater risk of subsequent ileostomy (Kaplan-Meier; p = 0.008). An independent RNAseq dataset validated the keratinization signature in a subset of pCD fistulae. Conclusion: Integrated multiomic analysis identified distinct molecular subtypes of pCD with surgical and therapeutic relevance. These findings refine the molecular understanding of pCD and support a precision medicine approach.

Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

Inflammatory bowel disease (IBD) is a chronic immune-mediated disorder of the gastrointestinal tract whose genetic basis is only partly resolved because most risk variants identified by genome-wide association studies (GWAS) lie in non-coding regions, limiting direct gene assignment and biological interpretation ^1,2 . Here we analysed whole-exome and whole-genome sequencing data from 86,213 IBD cases and 478,363 controls of European ancestry. We identified 68 IBD genes directly implicated by conditionally independent protein-coding associations across the allele frequency spectrum. Many newly implicated IBD genes are supported by orthogonal genomic or pleiotropic evidence, pointing to disease-related pathways and nominating targets with therapeutic relevance. We further identified allelic series and non-additive effects at key loci such as NOD2 and TYK2. These results show that large-scale sequencing can resolve disease genes and pathways that remain ambiguous from non-coding association alone, providing a more direct route from human genetics to biological insight and therapeutic hypotheses.

Background and Objective Systematic bias between therapeutic drug monitoring assays may lead to inappropriate treatment decisions in clinical practice. While such bias is well recognized, its impact on model-informed precision dosing remains unexplored. In this study, we evaluate how assay bias affects the predictive performance of population pharmacokinetic models, using ustekinumab in patients with Crohn’s disease as an example. Methods We repurposed data from 83 patients with Crohn’s disease. Ustekinumab concentrations were measured using both an homogeneous mobility shift assay and enzyme-linked immunosorbent assay. Two corresponding population pharmacokinetic models were developed. Bayesian forecasting was performed under matched and mismatched combinations of assay data and population pharmacokinetic models. Predictive accuracy and precision were assessed using relative bias and relative root mean square error, with predefined thresholds for clinical acceptability. Agreement between assays and clearance estimates was evaluated using Bland–Altman plots, Deming regression, and concordance correlation coefficients. Model prior flattening strategies were explored to mitigate mismatches between model priors and therapeutic drug monitoring data. Results Ustekinumab concentrations measured by the homogenous mobility shift assay were overall 8.1 mg/L higher than those measured by an enzyme-linked immunosorbent assay (95% confidence interval −23.6, 39.7). Clearance estimates from the homogenous mobility shift assay-based population pharmacokinetic model were systematically lower (0.107 L/day; relative standard error, 7.6%) compared with those from the enzyme-linked immunosorbent assay-based population pharmacokinetic model (0.235 L/day; relative standard error, 5.4%). When assay data and population pharmacokinetic models were matched, Bayesian forecasting yielded clinically acceptable predictions across all scenarios (relative bias <20%, 95% confidence interval including zero). Mismatched combinations led to reduced accuracy. Precision was highest using the homogenous mobility shift assay data, irrespective of the population pharmacokinetic model. Flattening strategies improved predictive performances in some mismatched scenarios but did not fully recover bias. Conclusions Assay bias has a clinically relevant impact on the predictive performance of model-informed precision dosing. Our findings underscore the importance of aligning the therapeutic drug monitoring assay format with the assay format used to build the population pharmacokinetic model to ensure accurate and clinically acceptable dosing predictions.

Infliximab is an established rescue therapy for patients with steroid-refractory acute severe ulcerative colitis (ASUC), yet optimal dosing strategies minimizing colectomy risk remain unclear. We aimed to develop a model-informed risk stratification algorithm to identify patients at high risk of colectomy within 90 days of initiating infliximab to support personalized dosing. We conducted a multicenter, retrospective population pharmacokinetics (popPK) and exposure–response study using data from patients with ASUC. A parametric time-to-event model was developed to characterize the 90-day colectomy risk. Patient characteristics and pharmacokinetic projections were evaluated as predictors. These modelling results informed the development of an algorithm for risk stratification and personalized infliximab rescue dosing. Seven medical centers contributed data from 72 patients with ASUC, yielding a total of 152 infliximab serum concentrations. Eleven patients underwent colectomy within 90 days. The strongest predictor of colectomy was the clearance-normalized exposure between weeks 2 and 4 (area under the concentration–time curve, AUC_w2-4 to Bayesian-forecasted infliximab clearance, CL), with an area under the receiver operating characteristic curve of 0.79 (95% confidence interval [CI], 0.52-1.00). The AUC_w2-4/CL ratio was calculated by individualizing the popPK model using the patient’s body weight, baseline C-reactive protein, and infliximab concentrations. Patients with a log-transformed AUC_w2-4/CL ratio < 5.79 were classified as high risk for colectomy (sensitivity 83%, specificity 85%). Overall classification accuracy was 85% (95% CI, 74-92). We developed a model-based dose–exposure–response framework to predict colectomy risk in ASUC. We integrated the algorithm into an interactive tool to enable individualized infliximab rescue therapy.

Immunometabolism exerts a bimodal action at the interface of extracellular immune response and intracellular metabolism, putting it at the center of many immune-mediated inflammatory disorders (IMIDs). Research has shown that immunometabolic pathways may act as a dual checkpoint for the inflammatory cycle to return the system to homeostasis by inactivating inflammatory pathways and shifting metabolism in favor of regulatory phenotypes. In addition, immunometabolic targets may act in non-immune cells such as epithelial and mesenchymal cells. Therefore, the therapeutic approach to targeting the uniquely robust mechanisms of immunometabolism may ameliorate aspects of IMIDs that remained to be addressed. Several emerging targets, including mitochondrial regulators (eg NLRX1), membrane-bound receptors (eg PLXDC2), and hormonal peptides (eg GLP-1), illustrate the diverse ways immunometabolism can be leveraged therapeutically. Preclinical models of inflammatory bowel disease (IBD) and other IMIDs have highlighted the bimodal immunoregulatory roles of these pathways. Preliminary clinical data support the potential utility of immunometabolic modulation, particularly in combination with existing therapies, to overcome the current therapeutic ceiling in clinical efficacy. Continued research is needed to validate the efficacy, safety, and mechanistic precision of immunometabolic agents across the spectrum of IMIDs.

Hidradenitis suppurativa (HS) is a chronic inflammatory disease characterized by recurring skin lesions. Despite ongoing research, the exact cause underlying initiation and progression of disease remains unknown. While prior research has linked the skin microbiota to HS pathology, the role of viruses has remained unexplored. To investigate the skin virome, metagenomic sequencing of viral particles was performed on 144 skin samples from 57 individuals (39 HS patients and 18 controls). It was found that the virome is not only linked to BMI, but also to the presence and severity of HS, marking a diverging viral profile in the progression of disease. Despite no differences in alpha-diversity, HS patients exhibited a significantly higher beta-diversity compared to healthy controls, indicating a more personalized virome with reduced viral sharing among patients. We identified distinct groups of commonly shared phages, referred to as the core phageome, associated with either healthy controls or patients. Healthy controls displayed a higher abundance of two core Caudoviricetes phages predicted to infect Corynebacterium and Staphylococcus , comprising normal skin commensals. In contrast, HS patients carried previously uncharacterized phages that were more prevalent in advanced stages of the disease, which likely infect Peptoniphilus and Finegoldia , known HS-associated pathogens. Interestingly, genes involved in superinfection exclusion and antibiotic resistance could be found in phage genomes of healthy controls and HS patients, respectively. In conclusion, we report the existence of distinct core phages that may have clinical relevance in HS pathology by influencing skin bacteria through mechanisms such as superinfection exclusion and antibiotic resistance. IMPORTANCE: An increasing body of research showed that the microbiome has an important role in complex human disease. In line with this, here, we analyzed a longitudinal HS cohort and found a relationship between the skin virome and HS pathology. This relationship was defined by distinct groups of phages associated with either healthy controls or HS patients, yet, in both instances, capable of enhancing bacterial fitness. In healthy individuals, these phages were widely shared, fostering symbiosis by ensuring stability of the commensal skin microbiota. Conversely, in HS patients, these phages revealed a more individualistic nature and could contribute to dysbiosis by providing antibiotic resistance genes to bacterial pathogens. Overall, these findings point to a potential clinical significance of the virome in understanding and addressing HS pathology.