RESUMEN
Background: Stool characteristics are used as a measure of ulcerative colitis (UC) disease activity, but they have not been validated against objective inflammation. We aimed to determine whether stool characteristics measured by trained artificial intelligence (AI) and physicians correlate with inflammation in UC. Methods: Patients hospitalized with acute severe UC (ASUC) were asked to capture images of all bowel movements using a smartphone application (Dieta®). Validated AI was used to measure five stool characteristics including the Bristol stool scale. Additionally, four physicians scored each image for blood amount, mucus amount, and whether stool was in a toilet or commode. AI measurements and mean physician scores were rank-normalized and correlated with rank-normalized CRP values using mixed linear regression models. Mann-Whitney tests were used to compare median CRP values of images with and without mucus and with and without blood. Results: We analyzed 151 stool images collected from 5 patients admitted with ASUC (mean age 42 years, 40% male). Overall, Bristol stool scale and fragmentation positively correlated with CRP, while stool consistency negatively correlated with CRP. The median CRP of images with mucus was higher than that of images without mucus. Conclusions: Smartphone application AI measurements of Bristol stool scale, stool consistency, and stool fragmentation significantly correlate with CRP values in hospitalized patients with ASUC. Additionally, median CRPs are higher when mucus is seen. Further training of smartphone-based AI algorithms to validate the association of stool characteristics with objective inflammation may yield a novel, noninvasive tool for UC disease monitoring.
RESUMEN
Colitis is characterized by an exacerbated intestinal immune response, but the genetic and other mechanisms regulating immune activation remain incompletely understood. In order to identify new pathways leading to colitis, we sought to identify genes with increased expression in the colons of patients that also are near loci identified by genome wide association studies (GWAS) associated with IBD risk. One such SNP, rs9557195 was of particular interest because it is within an intron of G-protein-coupled receptor (GPR) 183, known to be important for lymphocyte migration. Furthermore, this SNP is in close proximity to the gene encoding another G-protein coupled receptor, GPR18. Analyzing publicly available datasets, we found transcripts of GPR183 and GPR18 to be increased in colon biopsies from ulcerative colitis and Crohn's disease patients, and GPR183 was even more increased in patients resistant to TNF treatment. Expression of both genes also was increased in mouse models of colitis. Therefore, our aim was to understand if increased expression of these GPRs in the intestine is related to disease severity in colitis models. Here we investigated the role of these receptors in the T cell transfer model and the dextran sulfate sodium model. In the T cell transfer model, GPR183 expression on donor T cells, as well as on other cell types in the Rag-/- recipients, was not essential for severe colitis induction. Furthermore, deficiency in Rag-/- mice for the enzyme that synthesizes a cholesterol metabolite that is a major ligand for GPR183 also did not affect disease. Similarly, lack of GPR18 expression in T cells or other cell types did not affect colitis pathogenesis in the T cell transfer or in the dextran sulfate sodium model. Therefore, despite increased expression of transcripts for these genes in the intestine during inflammation in humans and mice, they are not required for disease severity in mouse models of colitis induced by chemical injury or T cell cytokines, perhaps due to redundancy in mechanisms important for homing and survival of lymphocytes to the inflamed intestine.