P923 The pre-treatment gut microbiome at adult IBD inception: Initial signals from the Birmingham inception cohort
Rimmer, P.(1)*;Cheesbrough, J.(1);Iqbal, A.(2);Sharma, N.(1);Iqbal, T.(1);Quraishi, N.(1);
(1)University Hospitals Birmingham NHS Foundation Trust, Gastroenterology, Birmingham, United Kingdom;(2)University of BIrmingham, Institute of Cardiovascular Sciences, Birmingham, United Kingdom;
Gut microbiome disruption and ‘dysbiosis’ is an established characteristic of IBD. The lack of treatment naïve and prospective longitudinal microbiome data makes it challenging to separate the influence of potential confounders. We present our preliminary microbiota analysis from a treatment naïve cohort of IBD patients seen in our rapid-access integrated clinical and research IBD inception clinic.
Stool collected in DNA Genotek OM-200 kits is brought to the first face to face pre-diagnosis outpatient review, alongside faecal calprotectin (FCAL). Metadata is collected prospectively with repeat samples collected longitudinally. Healthy controls were recruited separately. Stool microbial DNA was extracted with subsequent 16S rRNA PCR and sequencing. Diversity analysis and taxonomic classifications were performed in line with the QIIME2 workflow. Taxa with linear discriminant analysis (LDA) >2 at a P<0.05 were considered significant on LDA effect size (LEfSe) analysis. Correlation was evaluated with Kendall’s Tau coefficient.
Across sites, our clinics have seen 609 patients, with 256 enrolled in active research. We have banked 200 pre-treatment OM-200 stool samples from this cohort, with a further 45 samples from follow up visits. Of the first 49 samples sequenced, 31 were diagnosed with IBD (UC=18; CD=13). An independent cohort of 18 healthy controls were used for comparison. Median FCAL in the IBD cohort was 915ug/g (IQR 1499ug/g). Microbial composition in the IBD patients as assessed by Bray-Curtis distance matrix was significantly different compared to healthy controls (P<0.001). Alpha diversity (Shannon diversity index) was significantly lower in the IBD cohort when compared to healthy controls (P=0.01, Figure 1).
These differences in alpha and beta diversity were also observed with IBD subtypes (P<0.01). Patients with IBD had significantly lower relative abundance of multiple taxa belonging to the families Clostridiaceae, Lachnospiraceae, and Coriobacteriaceae and genus Ruminococcus, Butyricicoccus, Bifidobacterium, Blautia and Dorea, as displayed in Figure 2. The genuses Fusobacterium, Peptostreptococcus and Subdoligranulum positively correlated with FCAL levels whilst the genus Lachnobacterium negatively correlated (both P<0.05).
We present our preliminary index analysis of microbiome data in a unique treatment naïve IBD cohort. Our ongoing prospective longitudinal collection of clinical, microbial, immunological and metabolomic datasets will facilitate understanding of potential baseline prognostic indicators, predictive biomarkers for treatment response and relationship with disease activity. A further large batch of samples are submitted for sequencing and additional insights will follow.