P109 Using baseline Peripheral blood mononuclear cell (PBMC) transcriptomics of Crohn Disease patients receiving Ustekinumab treatment as a tool to assess potential response at 1 year
Granot, M.(1); Braun, T.(2); Efroni, G.(2); Fudim, E.(2);Yavzori, M.(2);Haj, O.(3); Ben-Horin, S.(3);Kopylov, U.(3);Haberman Ziv, Y.(1)*;
(1)The Edmond and Lily Safra Children’s Hospital- Sheba Medical Center- Tel-Hashomer, Pediatric Gastroenterology and Nutrition Unit, Ramat Gan, Israel;(2)Sheba Medical Center- Tel-Hashomer, The Pediatric Gastroenterology Unit and Sheba Microbiome Center, Ramat Gan, Israel;(3)Sheba Medical Center- Tel-Hashomer, Department of Gastroenterology, Ramat Gan, Israel;
Background
Ustekinumab, a monoclonal antibody to the p40 subunit of interleukin-12 and interleukin-23, is used to treat Crohn Disease (CD) and clinical remission after one year was observed in about 50% of patients. We aimed to identify predictors for clinical response using PBMC transcriptomics obtained from Crohn Disease patients just prior to Ustekinumab treatment initiation.
Methods
RNA extraction from leukocytes was performed using Qiagen AllPrep RNA/DNA Mini Kit, followed by PolyA-RNA selection, fragmentation, cDNA synthesis, adaptor ligation, TruSeq RNA sample library preparation (Illumina, San Diego, CA), and paired-end 75bp sequencing. mRNA genes with transcripts per million (TPM) values above 1 in at least 20% of the samples were used. Differential gene expression was performed using DESeq2.
Results
We processed blood samples from 36 CD patients (13 males, [36%], median age 35 [IQR 29-41] years). Samples were obtained at baseline just before starting Ustekinumab treatment. 22/36 (61%) were define as responders and 14/36 (39%) as non-responders after 1 year based on Physician Global Assessment (PGA). Small bowel disease was significantly more common among responders 82% versus 36%, p=0.004. Principal component analysis (PCA) using the 12773 genes that passed expression filtering showed partial separation (Fig. 1).
Differential gene expression between responders (n=22) and non-responders (n=14), did not show gene expression signature that passed FDR correction, however the analyses identified 68 genes including CXCL1/2/3 that were induced in non-responders vs. responders with p<0.05 and fold change above 1.5. Functional annotation enrichments of these 68 genes using ToppGene indicated enrichment (Fig. 2) for cytokine activity (FDR=1.98E-05), CXCR chemokine receptor binding (FDR=2.11E-05), Interleukin-10 signaling (FDR=5.03E-07), Genes encoding secreted soluble factors (FDR=1.73E-05), Myeloid Cells, granulocytes CD11b+ (FDR=6.64E-12), and Myeloid Cells Dendritic cells (FDR=1.80E-08).
Conclusion
No strong differences were found in the blood transcriptomics between responders and non-responders. However, among the non-responders we noted an increased inflammatory response enriched for pathways linked with cytokine activity and chemokine receptor binding and innate granulocytes and Myeloid signature. A larger cohort is required to validate and farther explore these findings.
Fig. 1: Principal component analysis (PCA) using the 12773 genes that passed expression filtering showed partial separation. 
Fig. 2: Functional annotation enrichments of the 68 genes induced in PBMC. 