Adenoma to Colorectal Cancer Estimated Transition Rates Stratified by BMI Categories—A Cross-Sectional Analysis of Asymptomatic Individuals from Screening Colonoscopy Program

Most colorectal cancers (CRC) assumedly develop from precursor lesions, i.e., colorectal adenomas (adenoma-carcinoma sequence). Epidemiological and clinical data supporting this hypothesis are limited. Therefore, the aim of the present study is to estimate relative dynamics of colorectal adenoma-carcinoma sequence for groups of screenees stratified by BMI (body mass index) based on prevalence data from Polish Colonoscopy Screening Program (PCSP). We performed a cross-sectional analysis of database records of individuals who entered the national opportunistic colonoscopy screening program for CRC in Poland. We calculated prevalence of adenomas and CRCs adjusted for sex, 5-year age group, family history of CRC, smoking, diabetes and use of aspirin, hormonal therapy and proton-pump inhibitors use. Thereafter we calculated estimated transition rate (eTR) with confidence intervals (CIs) defined as adjusted prevalence of more advanced lesion divided by adjusted prevalence of less advanced lesion. All analyzes were stratified according to the BMI categories: normal (BMI 18.0 to <25.0), overweight (BMI 25.0 to <30.0) and obese (BMI ≥ 30.0). Results are reported in the same respective order. After exclusions we performed analyses on 147 385 individuals. We found that prevalence of non-advanced adenomas is increasing with BMI category (12.19%, 13.81%, 14.70%, respectively; p < 0.001). Prevalence of advanced adenomas was increasing with BMI category (5.20%, 5.77%, 6.61%, respectively; p < 0.001). Early CRCs prevalence was the highest for obese individuals (0.55%) and the lowest for overweight individuals (0.44%) with borderline significance (p = 0.055). For advanced CRC we found that prevalence seems to be inversely related to BMI category, however no statistically significant differences were observed (0.35%, 0.31%, 0.28%; p = 0.274). eTR for non-advanced adenoma to advanced adenoma is higher for obese individuals than for overweight individuals with bordering CIs (42.65% vs. 41.81% vs. 44.95%) eTR for advanced adenoma to early CRC is highest for normal individuals, however CIs are overlapping with remaining BMI categories (9.02% vs. 7.67% vs. 8.39%). eTR for early CRC to advanced CRC is lower for obese individuals in comparison to both normal and overweight individuals with marginally overlapping CIs (73.73% vs. 69.90% vs. 50.54%). Obese individuals are more likely to develop adenomas, advanced adenomas and early CRC but less likely to progress to advanced CRC. Therefore, this study provides new evidence that obesity paradox exists for colorectal cancer.

A Novel Approach Towards Less Invasive Multi ‘Omics Gut Analyses: A Pilot Study

Newer ‘omics approaches such as metatranscriptomics and metabolomics allow functional assessments of the interaction(s) between the gut microbiome and the human host. In order to generate meaningful data with these approaches, though, the method of sample collection is critical. Prior studies have relied upon expensive and invasive means towards sample acquisition such as intestinal biopsy, while other studies have relied upon easier methods of collection such as fecal samples that do not necessarily represent those microbes in contact with the host. In this pilot study, we attempt to characterize a novel, minimally invasive method towards sampling the human microbiome using mucosal cytology brush sampling compared to intestinal gut biopsy on 5 healthy participants undergoing routine screening colonoscopy. We compared metatranscriptomic analyses between the two collection methods, identifying increased taxonomic evenness and beta diversity in the cytology brush samples, and similar community transcriptional profiles between the two methods. Metabolomics assessment demonstrated striking differences between the two methods, implying a difference in bacterial-derived versus human absorbed metabolites. Put together, this study supports the use of a less invasive method of microbiome sampling with cytology brushes, but caution must be exercised when performing metabolomics assessment as this represents differential metabolite production but not absorption by the host.

Artificial Intelligence in Endoscopy

<b><i>Background:</i></b> Owing to their rapid development, artificial intelligence (AI) technologies offer a great promise for gastroenterology practice and research. At present, AI-guided image interpretation has already been used with success for endoscopic detection of early malignant lesions. Nonetheless, there are complex challenges and possible shortcomings that must be considered before full implementation can be realized. <b><i>Summary:</i></b> In this review, the current status of AI in endoscopy is summarized. Future perspectives and open questions for further studies are stressed. <b><i>Key Messages:</i></b> The usage of AI algorithms for polyp detection in screening colonoscopy results in a significant increase in the adenoma detection rate, mainly attributed to the identification of diminutive polyps. Computer-aided characterization of colorectal polyps accompanies the detection, but further studies are needed to evaluate the clinical benefit. In contrast to colonoscopy, usage of AI in gastroscopy is currently rather limited. Regarding other fields of endoscopic imaging, capsule endoscopy is the ideal imaging platform for AI, due to the potential of saving time in the video analysis.