scholarly journals Single-cell analysis of colonic epithelium reveals unexpected shifts in cellular composition and molecular phenotype in treatment-naïve adult Crohn’s disease

2021 ◽  
Author(s):  
Matt Kanke ◽  
Meaghan M. Kennedy ◽  
Sean Connelly ◽  
Matthew Schaner ◽  
Michael T. Shanahan ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Single Cell ◽  
Association Studies ◽  
Paneth Cell ◽  
Genome Wide Association Studies ◽  
Intestinal Epithelial ◽  
Cell Type ◽  
Aberrant Expression ◽  
Treatment Naïve

AbstractThe intestinal epithelial barrier is comprised of a monolayer of specialized intestinal epithelial cells (IECs) that are critical in maintaining gut mucosal homeostasis. Dysfunction within various IEC fractions can increase intestinal permeability, resulting in a chronic and debilitating condition known as Crohn’s disease (CD). Defining the molecular changes in each IEC type in CD will contribute to an improved understanding of the pathogenic processes and the identification of potential therapeutic targets. Here we performed, for the first time at single-cell resolution, a direct comparison of the colonic epithelial cellular and molecular landscape between treatment-naïve adult CD and non-IBD control patients. Our analysis revealed that in CD patients there is a significant skew in the colonic epithelial cellular distribution away from canonical LGR5+ stem cells, located at the crypt-bottom, and toward one specific subtype of mature colonocytes, located at the crypt-top. Further analysis revealed unique changes to gene expression programs in every major cell type, including a previously undescribed suppression in CD of most enteroendocrine driver genes as well as L-cell markers including GCG. We also dissect a previously poorly understood SPIB+ cell cluster, revealing at least four sub-clusters that exhibit unique features. One of these SPIB+ sub-clusters expresses crypt-top colonocyte markers and is significantly up-regulated in CD, whereas another sub-cluster strongly expresses and stains positive for lysozyme (albeit no other canonical Paneth cell marker), which surprisingly is greatly reduced in expression in CD. Finally, through integration with data from genome-wide association studies, we show that genes implicated in CD risk exhibit heretofore unknown cell-type specific patterns of aberrant expression in CD, providing unprecedented insight into the potential biological functions of these genes.

scholarly journals Revealing immune responses in the Mycobacterium avium subsp. paratuberculosis-infected THP-1 cells using single cell RNA-sequencing

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254194
Author(s):  
Hong-Tae Park ◽  
Woo Bin Park ◽  
Suji Kim ◽  
Jong-Sung Lim ◽  
Gyoungju Nah ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Single Cell ◽  
Mycobacterium Avium ◽  
Expression Patterns ◽  
Cell Types ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Cytokines And Chemokines

Mycobacterium avium subsp. paratuberculosis (MAP) is a causative agent of Johne’s disease, which is a chronic and debilitating disease in ruminants. MAP is also considered to be a possible cause of Crohn’s disease in humans. However, few studies have focused on the interactions between MAP and human macrophages to elucidate the pathogenesis of Crohn’s disease. We sought to determine the initial responses of human THP-1 cells against MAP infection using single-cell RNA-seq analysis. Clustering analysis showed that THP-1 cells were divided into seven different clusters in response to phorbol-12-myristate-13-acetate (PMA) treatment. The characteristics of each cluster were investigated by identifying cluster-specific marker genes. From the results, we found that classically differentiated cells express CD14, CD36, and TLR2, and that this cell type showed the most active responses against MAP infection. The responses included the expression of proinflammatory cytokines and chemokines such as CCL4, CCL3, IL1B, IL8, and CCL20. In addition, the Mreg cell type, a novel cell type differentiated from THP-1 cells, was discovered. Thus, it is suggested that different cell types arise even when the same cell line is treated under the same conditions. Overall, analyzing gene expression patterns via scRNA-seq classification allows a more detailed observation of the response to infection by each cell type.

scholarly journals A Genome-wide Association Study Identifying RAP1A as a Novel Susceptibility Gene for Crohn’s Disease in Japanese Individuals

2018 ◽  
Vol 13 (5) ◽  
pp. 648-658 ◽  
Author(s):  
Yoichi Kakuta ◽  
Yosuke Kawai ◽  
Takeo Naito ◽  
Atsushi Hirano ◽  
Junji Umeno ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Mononuclear Cells ◽  
Association Studies ◽  
Susceptibility Gene ◽  
Genome Wide Association ◽  
Effector Memory ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Abstract Background and Aims Genome-wide association studies [GWASs] of European populations have identified numerous susceptibility loci for Crohn’s disease [CD]. Susceptibility genes differ by ethnicity, however, so GWASs specific for Asian populations are required. This study aimed to clarify the Japanese-specific genetic background for CD by a GWAS using the Japonica array [JPA] and subsequent imputation with the 1KJPN reference panel. Methods Two independent Japanese case/control sets (Tohoku region [379 CD patients, 1621 controls] and Kyushu region [334 CD patients, 462 controls]) were included. GWASs were performed separately for each population, followed by a meta-analysis. Two additional replication sets [254 + 516 CD patients and 287 + 565 controls] were analysed for top hit single nucleotide polymorphisms [SNPs] from novel genomic regions. Results Genotype data of 4 335 144 SNPs from 713 Japanese CD patients and 2083 controls were analysed. SNPs located in TNFSF15 (rs78898421, Pmeta = 2.59 × 10−26, odds ratio [OR] = 2.10), HLA-DQB1 [rs184950714, pmeta = 3.56 × 10−19, OR = 2.05], ZNF365, and 4p14 loci were significantly associated with CD in Japanese individuals. Replication analyses were performed for four novel candidate loci [p <1 × 10−6], and rs488200 located upstream of RAP1A was significantly associated with CD [pcombined = 4.36 × 10−8, OR = 1.31]. Transcriptome analysis of CD4+ effector memory T cells from lamina propria mononuclear cells of CD patients revealed a significant association of rs488200 with RAP1A expression. Conclusions RAP1A is a novel susceptibility locus for CD in the Japanese population.

Association between genome-wide association studies reported SNPs and pediatric-onset Crohn’s disease in Canadian children

2010 ◽  
Vol 128 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Devendra K. Amre ◽  
David R. Mack ◽  
Kenneth Morgan ◽  
David Israel ◽  
Colette Deslandres ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Pediatric Onset

scholarly journals Inferring relevant tissues and cell types for complex traits in genome-wide association studies

2021 ◽  
Author(s):  
Rujin Wang ◽  
Danyu Lin ◽  
Yuchao Jiang
Keyword(s):  
Single Cell ◽  
Complex Traits ◽  
Association Studies ◽  
Cell Types ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Disease Etiology ◽  
Genome Wide ◽  
Cell Type Specific

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific omics measurements from single-cell sequencing. We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant tissues or cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We extend our framework to single-cell transcriptomic data and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and single-cell datasets and further validated using PubMed search and existing bulk case-control testing results.

scholarly journals Identifying Crohn’s disease signal from variome analysis

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Yanran Wang ◽  
Maximilian Miller ◽  
Yuri Astrakhan ◽  
Britt-Sabina Petersen ◽  
Stefan Schreiber ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Prediction Models ◽  
Association Studies ◽  
Model Performance ◽  
Disease Genes ◽  
Analysis Tool ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Diagnostic Time

Abstract Background After years of concentrated research efforts, the exact cause of Crohn’s disease (CD) remains unknown. Its accurate diagnosis, however, helps in management and preventing the onset of disease. Genome-wide association studies have identified 241 CD loci, but these carry small log odds ratios and are thus diagnostically uninformative. Methods Here, we describe a machine learning method—AVA,Dx (Analysis of Variation for Association with Disease)—that uses exonic variants from whole exome or genome sequencing data to extract CD signal and predict CD status. Using the person-specific coding variation in genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. By additionally accounting for batch effects, we were able to accurately predict CD status for thousands of previously unseen individuals from other panels. Results AVA,Dx highlighted known CD genes including NOD2 and new potential CD genes. AVA,Dx identified 16% (at strict cutoff) of CD patients at 99% precision and 58% of the patients (at default cutoff) with 82% precision in over 3000 individuals from separately sequenced panels. Conclusions Larger training panels and additional features, including other types of genetic variants and environmental factors, e.g., human-associated microbiota, may improve model performance. However, the results presented here already position AVA,Dx as both an effective method for revealing pathogenesis pathways and as a CD risk analysis tool, which can improve clinical diagnostic time and accuracy. Links to the AVA,Dx Docker image and the BitBucket source code are at https://bromberglab.org/project/avadx/.

scholarly journals Identifying Crohn’s disease signal from variome analysis

2017 ◽  
Author(s):  
Yanran Wang ◽  
Yuri Astrakhan ◽  
Britt-Sabina Petersen ◽  
Stefan Schreiber ◽  
Andre Franke ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Prediction Models ◽  
Disease Risk ◽  
Association Studies ◽  
Disease Genes ◽  
Analysis Tool ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Diagnostic Time

AbstractBackgroundAfter many years of concentrated research efforts, the exact cause of Crohn’s disease remains unknown. Its accurate diagnosis, however, helps in management and even preventing the onset of disease. Genome-wide association studies have identified 140 loci associated with CD, but these carry very small log odds ratios and are uninformative for diagnoses.ResultsHere we describe a machine learning method – AVA,Dx (Analysis of Variation for Association with Disease) – that uses whole exome sequencing data to make predictions of CD status. Using the person-specific variation in these genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. In this panel, our models differentiate CD patients from healthy controls with 71% precision and 73% recall at the default cutoff. By additionally accounting for batch effects, we are also able to predict individual CD status for previously unseen individuals from a separate CD study (84% precision, 73% recall).ConclusionsLarger training panels and additional features, including regulatory variants and environmental factors, e.g. human-associated microbiota, are expected to improve model performance. However, current results already position AVA,Dx as both an effective method for highlighting pathogenesis pathways and as a simple Crohn’s disease risk analysis tool, which can improve clinical diagnostic time and accuracy.

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