Dataset Information

Inherent Immune Cell Variation Within Colonic Segments Presents Challenges for Clinical Trial Design.

ABSTRACT:

Background and aims

Intestinal biopsy sampling during IBD trials represents a valuable adjunct strategy for understanding drug responses at the tissue level. Given the length and distinctive embryonic origins of the proximal and distal colon, we investigated whether inherent regional differences of immune cell composition could introduce confounders when sampling different disease stages, or pre/post drug administration. Here, we capitalise on novel mass cytometry technology to perform deep immunophenotyping of distinct healthy colonic segments, using the limited numbers of biopsies that can be harvested from patients.

Methods

Biopsies [2.8 mm] were collected from the caecum, transverse colon, descending colon, and rectum of normal volunteers. Intestinal leukocytes were isolated, stained with a panel of 37 antibodies, and mass cytometry data acquired.

Results

Site-specific patterns of leukocyte localisation were observed. The proximal colon featured increased CD8+ T cells [particularly resident memory], monocytes, and CD19+ B cells. Conversely, the distal colon and rectum tissues exhibited enrichment for CD4+ T cells and antibody-secreting cells. The transverse colon displayed increased abundance of both γδ T cells and NK cells. Subsets of leukocyte lineages also displayed gradients of expression along the colon length.

Conclusions

Our results show an inherent regional immune cell variation within colonic segments, indicating that regional mucosal signatures must be considered when assessing disease stages or the prospective effects of trial drugs on leukocyte subsets. Precise protocols for intestinal sampling must be implemented to allow for the proper interpretation of potential differences observed within leukocyte lineages present in the colonic lamina propria.

SUBMITTER: Tyler CJ

PROVIDER: S-EPMC7533898 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Abstract Background The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference. Methods We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage. Results Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0–40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17–208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02–1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28–.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23–1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants. Conclusions Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Project description:Biopsy remains the gold-standard measure for staging liver disease, both to inform prognosis and to assess the response to a given treatment. Semiquantitative scores such as the Ishak fibrosis score are used for evaluation. These scores are utilised in clinical trials, with the US Food and Drug Administration mandating particular scores as inclusion criteria for participants and using the change in score as evidence of treatment efficacy. There is an urgent need for improved, quantitative assessment of liver biopsies to detect small incremental changes in liver architecture over the course of a clinical trial. Artificial intelligence (AI) methods have been proposed as a way to increase the amount of information extracted from a biopsy and to potentially remove bias introduced by manual scoring. We have trained and evaluated an AI tool for measuring the amount of scarring in sections of picrosirius red-stained liver. The AI methodology was compared with both manual scoring and widely available colour space thresholding. Four sequential sections from each case were stained on two separate occasions by two independent clinical laboratories using routine protocols to study the effect of inter- and intra-laboratory staining variation on these tools. Finally, we compared these methods to second harmonic generation (SHG) imaging, a stain-free quantitative measure of collagen. Although AI methods provided a modest improvement over simpler computer-assisted measures, staining variation both within and between laboratories had a dramatic effect on quantitation, with manual assignment of scar proportion being the most consistent. Manual assessment also most strongly correlated with collagen measured by SHG. In conclusion, results suggest that computational measures of liver scarring from stained sections are compromised by inter- and intra-laboratory staining. Stain-free quantitative measurement using SHG avoids staining-related variation and may prove more accurate in detecting small changes in scarring that may occur in therapeutic trials.