Introduction

As well as having a major impact on bone metabolism, vitamin D (vitD) is recognised as an immunomodulatory hormone with a pivotal role in the pathogenesis of inflammatory bowel disease (IBD). Low vitD levels in patients with IBD are associated with active inflammation, disease severity, poor quality of life and adverse clinical outcomes. Furthermore, lower vitD levels in patients with IBD were shown to be associated with higher pro-inflammatory cytokine profiles. Therefore, it is plausible that vitD may have use as a therapeutic agent in IBD. Our previous work suggests that pre-treatment with vitD may improve effectiveness of biologic drugs such as TNF-α inhibitors and the anti-integrin agent vedolizumab (VDZ). However, data in this context is limited.

Aims & Methods

The aim of this study was to explore potential effects of serum vitD levels on biologic treatment response in IBD patients. A retrospective cohort study was conducted to monitor ambulant treatment of IBD patients with biologics in relationship to their vitD levels. Medical records and routine blood and stool samples of 162 adult IBD patients were assessed at therapy start and 8-weekly thereafter. Samples were analysed for standard blood count, total 25OHD, albumin and inflammation parameters (hsCRP, ESR and faecal calprotectin (FC)) by standard methods. Biologic treatments (infliximab (IFX), its biosimilars (IFX-s), VDZ and ustekinumab (UST)) were administered over 1 year. Drug and anti-drug antibody (ADA) levels were measured with systems provided by Immundiagnostik AG, Bensheim, Germany. VitD values were dichotomized into deficient (≤ 30ng/mL) and sufficient (>30ng/mL). A positive treatment response was defined according to evidence of inflammation as shown by change in hsCRP-levels from baseline to the last two samples monitored. IBM SPSS Statistics 24 was used for statistical analysis.

Results

162 patients with IBD (91 with Crohn’s disease (CD)/ 71 with ulcerative colitis (UC); 81 f/81 m; age 40.2±11.5y) were enrolled. At baseline, 40.7 % used vitD supplementation, 10.5 % were biologic naïve and 50.6 % were vitD deficient. No conclusive relations were found between baseline vitD or supplementation status with drug or ADA levels. However, higher vitD levels over time were associated with positive treatment response for patients on IFX and UST (p<0.05). Treatment specific analysis revealed no significant associations between drug TCs and overall vitD status or treatment response. In descriptive analysis, pre-treatment vitD status was not associated with demographic or clinical characteristics but positively associated with mean corpuscular volume (MCV) and FC and inversely related to transferrin. Ultimately, 72.8 % of patients responded to biologic treatment. Response was related to disease location in CD (p = 0.011) and positively associated with naivety to biologics (p = 0.040). Treatment responders had significantly higher Hb, iron, TSAT and significantly lower ESR, hsCRP and FC.

Conclusion

Our results support a protective role of vitD in IBD patients treated with the biologic agents IFX and UST, shown here for the first time for UST. Interestingly, not the initial vitD status, but permanently sufficient vitD levels were decisive for improved treatment response. Therefore, regular vitD monitoring and long-term vitD substitution in patients with low vitD levels is indicated.

Disclosure

Olivia Schütte, Lea Tessmer and Julia Stötzel have nothing to disclose. Aysegül Aksan is an employee of Immundiagnostik AG.
Oliver Schröder: Lecturing fees: Abbvie, Falk, Janssen, Takeda, Norgine and Pfizer. Congress expenses: Falk, Pfizer.
Jürgen Stein: Consulting: Abbvie, Bristol Myers Squibb, Dr Schär, Falk, Ferring, Fresenius Kabi, Immundiagnostik, Janssen, Medice, MSD, Pfizer, Pharmacosmos, Shire, Takeda, Thermofisher, Vifor. Board member: Abbvie, Bristol Myers Squibb, Dr Schär, Ferring, Fresenius Kabi, Immundiagnostik, Janssen, MSD, NPS, Pharmacosmos, Takeda, Vifor and Shield. Lecturing fees: Vifor Pharma

Introduction

Differential diagnosis of solid pancreatic tumours (SPT) is a clinical challenge. Development of advanced imaging techniques associated with EUS, such as elastography and contrast enhancement, has been a step forward in this context. EUS-guided detective flow imaging (DFI) is a very recent technology allowing the evaluation of microvascularization and low-velocity blood flow without the need of contrast agents.

Aims & Methods

Aim of our study was to evaluate the findings obtained by EUS-DFI in SPT and compare them with contrast enhanced harmonic EUS (CEH-EUS).
Methods: A prospective, single-centre, observational study in patients who underwent EUS for the evaluation of SPT was designed. Procedures were performed with a linear echoendoscope (Fujifilm 740UT) attached to the ultrasound system Arietta 850. Lesions were characterized according to the vascularization pattern (hypervascular, isovascular and hypovascular) described with both methods. Final diagnosis was based on histology after EUS-guided biopsy. Data area shown as mean ± SD and percentage.

Results

44 patients were included (mean age 67 years, range 24-88, 23 males). Mean tumour size was 26.1 ± 15.7 mm. Fourteen (31.8%) lesions were located in the head of the pancreas, 19 (43.2%) in the body, 9 (20.5%) in the tail and 2 (4.5%) in the uncinate process. Final diagnosis was adenocarcinoma in 24 patients (54.5%), neuroendocrine tumour in 13 (29.5%), inflammatory mass in 3 (6.8%), autoimmune pancreatitis in 1 (2.3%), pancreatic necrosis in 1 (2.3%), accessory spleen in 1 (2.3%) and lipoma in 1 (2.3%). Agreement regarding the vascular pattern of SPT between CEH-EUS and EUS-DFI was reached in 97.7% of the cases. All adenocarcinomas were hypovascular, inflammatory masses and autoimmune pancreatitis isovascular, pancreatic necrosis avascular, and accessory spleen and lipoma hypervascular at both CEH-EUS and EUS-DFI. All 13 neuroendocrine tumours were hypervascular at CEH-EUS, 12 of them (90%) at EUS-DFI.

Conclusion

EUS-DFI allows evaluating the microvascular pattern of SPT with a similar accuracy than CEH-EUS, but without the need of using contrast agents.

Disclosure

Julio Iglesias-Garcia. Advisor Pentax, FujiFilm, Mediglobe

Introduction

Bowel urgency is a common and disruptive symptom in patients with ulcerative colitis (UC).¹ Fatigue is also common and has been associated with greater disease activity and lower quality of life in these patients.² However, little is known regarding the relationship between bowel urgency remission, bowel urgency clinically meaningful improvement, rectal bleeding remission, or stool frequency remission and improvement in fatigue. We examined the association between bowel urgency remission or bowel urgency clinically meaningful improvement and Fatigue Numeric Rating Scale (NRS) scores in the presence of rectal bleeding remission or stool frequency remission using pooled data from LUCENT-1 (NCT03518086) and LUCENT-2 (NCT03524092) phase 3 trials.

Aims & Methods

Bowel urgency was assessed by the Urgency NRS (UNRS), ranging from 0 (no urgency) to 10 (worst possible urgency). Bowel urgency remission was defined as a UNRS score of 0 or 1; bowel urgency clinically meaningful improvement was defined as a ≥3-point decrease in UNRS score from baseline.³ Rectal bleeding remission was defined as a modified Mayo subscore of 0; stool frequency remission was defined as a subscore of 0 or 1 with ≥1-point decrease from baseline.⁴ Fatigue was assessed by the Fatigue NRS, ranging from 0 (no fatigue) to 10 (worst possible fatigue), using change from baseline in Fatigue NRS score. Mediation analyses were performed to separately examine the relative association between the direct effects of bowel urgency remission and bowel urgency clinically meaningful improvement (predictor variables) and Fatigue NRS scores while adjusting for rectal bleeding remission and stool frequency remission (mediation variables). Analyses were treatment agnostic and combined mirikizumab and placebo treatment groups from LUCENT-1 (N=1162) and LUCENT-2 (N=544).

Results

The direct effect of bowel urgency remission at Week 12 and Week 40 (52 weeks continuous treatment) accounted for 68.3% and 62.1%, respectively, of the improvement in change from baseline in Fatigue NRS score. Substantially greater proportions of the Fatigue NRS score improvements were related to bowel urgency remission versus rectal bleeding remission (Week 12: 13.4% and Week 40: 16.4%) or stool frequency remission (Week 12: 18.3% and Week 40: 21.5%). Results were similar for bowel urgency clinically meaningful improvement at Week 12 (91.8%) and Week 40 (87.4%).

Conclusion

These findings provide strong evidence for a direct association between improvement or remission in bowel urgency and improvement in fatigue in patients with moderately-to-severely active UC.

References

1. Hibi T, et al. Inflamm Intest Dis. 2020;5(1):27.
2. Regueiro MD, et al. Adv Ther. Online Nov 12, 2022. doi: 10.1007/s12325-022-02364-2.
3. Dubinsky MC, et al., J Patient Rep Outcomes. 2022;6(1):114.
4. ClinicalTrials.gov. Updated October 27, 2022. Access December 1, 2022. clinicaltrials.gov/ct2/show/NCT03518086.

Disclosure

D. T. Rubin has been a consultant for and/or received research grants from: AbbVie, AbGenomics, Allergan, Biomica, Boehringer Ingelheim, Bristol Myers Squibb, Celgene/Syneos Health, Check-Cap, Dizal Pharma, Eli Lilly and Company, Galen/Atlantica, Genentech/Roche, Gilead Sciences, GlaxoSmithKline, Ichnos Sciences, InDex Pharmaceuticals, Janssen, Narrow River Management, Pfizer, Prometheus Therapeutics and Diagnostics, Reistone Biopharma, Shire, Takeda, and TechLab; is a shareholder at: AbGenomics and Biomica; is on the Board of Trustees at: American College of Gastroenterology; is cofounder and CFO of: Cornerstones Health (non-profit); and is cofounder of: GoDuRn; P. Hindryckx has received consulting fees from: AbbVie, Boston Scientific, Eli Lilly and Company, Janssen, Taewoong Medical, and Takeda; has received speaker fees from: AbbVie, Chiesi, Dr. Falk Pharma, Ferring Pharmaceuticals, Takeda, Tillotts Pharma AG, and Vifor Pharma; and has received research support from: Eli Lilly and Company; T. Hibi has received lecture fees from: AbbVie, EA Pharma, Janssen, JIMRO, Mitsubishi Tanabe Pharma, Mochida Pharmaceutical, Pfizer, Sand K.K., Takeda, and Zeria Pharmaceutical; has received advisory and/or consultancy fees from: AbbVie, Celltrion, EA Pharma, Eli Lilly and Company, Gilead Sciences, Janssen, Mitsubishi Tanabe Pharma, Nichi-Iko Pharmaceutical, Nippon Kayaku, Takeda, and Zeria Pharmaceutical; has received research grants from: AbbVie, Activaid, Alfresa Pharma, Bristol Myers Squibb, Eli Lilly Japan K.K., Ferring Pharmaceuticals, Gilead Sciences, Janssen Pharmaceutical K.K., JMDC, Mochida Pharmaceutical, Nippon Kayaku, Pfizer Japan Inc., and Takeda; has received scholarship•contributions from: Mitsubishi Tanabe Pharma, Nippon Kayaku, Pfizer Japan Inc., and Zeria Pharmaceutical; has belonged to study group sponsorship by: Alfresa Pharma, JIMRO, Kyorin, and Mochida Pharmaceutical; and has received grants and/or funds from: MIYARISAN Pharmaceutical Co., Ltd. and Zeria Pharmaceutical; K. McGinnis, T. Hunter Gibble, and A. Keohane are employees and shareholders of:
Eli Lilly and Company; M. Regueiro has received consulting fees from: AbbVie, Allergan, Amgen, Celgene, Eli Lilly and Company, Genentech, Gilead Sciences, Janssen, Miraca Life Sciences, Pfizer, Prometheus Therapeutics and Diagnostics, Salix Pharmaceuticals, Seres Therapeutics, Takeda, Target RWE, and UCB Pharma; and has received research support from: AbbVie, Janssen, Pfizer, and Takeda

Introduction

Immuno-mediated colitis is one of the most common gastrointestinal side effects associated with immune checkpoint inhibitors (ICIs). ICIs-colitis shares with inflammatory bowel disease (IBD), including both Crohn’s Disease (CD) and Ulcerative Colitis (UC), the clinical presentation, macroscopic, microscopic, and serological findings, making challenging the differentiation between the two conditions. The gut microbiota has been suggested as an important driver in the pathogenesis of ICIs-colitis as well as in the pathogenesis of IBD. We aimed to assess whether a specific microbiota profile, as measured by a machine learning approach, can be associated with ICIs-colitis and whether it differs from the one assessed in patients with IBD and in healthy controls (HCs).

Aims & Methods

In this prospective pilot study, consecutive patients with ICIs-colitis, patients with IBD and HCs were enrolled. Stool samples were collected for fecal microbiota assessment analysis by 16S rRNA gene sequencing approach. The raw reads underwent a filtering procedure performed within QIIME2 analysis framework (version 2022.8). Alpha diversity was evaluated on rarefied counts (Richness, Shannon, and Pielou indices; rarefaction level: 31,556), while beta diversity was calculated on normalized counts (Bray-Curtis, Jaccard, Canberra, Weighted and Unweighted Unifrac; counts normalized with GMPR). The diversity analysis was conducted in R (version 4.1.0). A permutational analysis of variance (PERMANOVA) test on Bay-Curtis dissimilarity was used to test for differences in the microbiota composition between disease status groups (vegan and ecole packages). The MaAsLin2 package was then used to perform differential abundance analysis at all taxonomic levels. Supervised and unsupervised machine learning algorithms were applied.

Results

Nineteen patients with ICIs-colitis, 40 patients with UC (20 active and 20 inactive), 34 with CD (14 active and 20 inactive) and 36 HC were enrolled. Alpha diversity was not significantly different between ICIs-colitis and HCs (p=0.94), while it was statistically significant between IBD and HCs (p=0.02) and between IBD and ICIs-colitis (p=0.03). At phylum levels, we found high levels of Tenericutes in HCs and high levels of Proteobacteria in ICIs-colitis. Moreover, we found high levels of Actinobacteria in IBD compared to the other group. Interestingly, at genus levels, we found very high levels of Enhydrobacters in ICIs-colitis compared to patients with IBD. While at species levels, high levels of Bifidobacterium longum in patients with UC were observed. A specific microbiota profile was found for each group (IBD, ICIs, HC) and was confirmed with sparse partial least squares discriminant analysis, a machine learning-supervised approach. The latter allowed us to observe a perfect class prediction and group separation using the complete information (full Operational Taxonomic Unit table), with a minimal loss in performance when using only 5% of features.

Conclusion

A machine learning approach to 16S rRNA data identifies a bacterial signature characterizing ICIs-colitis from IBD and HCs. Future research will clarify whether such microbiota profiling is useful for prediction, early diagnosis and management of patients with ICIs-colitis.

Disclosure

None