| Literature DB >> 30979947 |
Stephen J Walker1,2, Carl D Langefeld3,4, Kip Zimmerman3,4, Marshall Z Schwartz3,5, Arthur Krigsman6.
Abstract
In children with autism spectrum disorder (ASD) who present to the gastroenterologist with chronic constipation on a background of colonic inflammation, we have identified two distinct clinical subtypes: (1) patients who experience a sustained state of GI symptomatic remission while on maintenance anti-inflammatory therapy (fast responders) and, (2) those with recurrent right-sided fecal loading requiring regular colon cleanouts during treatment for enterocolitis (slow responders). We hypothesized that a detailed molecular analysis of tissue from the affected region of the colon would provide mechanistic insights regarding the fast versus slow response to anti-inflammatory therapy. To test this, ascending colon biopsy tissues from 35 children with ASD (20 slow responders and 15 fast responders) were analyzed by RNAseq. Hierarchical cluster analysis was performed to assign samples to clusters and gene expression analysis was performed to identify differentially expressed transcripts (DETs) between samples within the clusters. Significant differences were found between the two clusters with fast responder-predominant cluster showing an upregulation of transcripts involved in the activation of immune and inflammatory response and the slow responder-predominant cluster showing significant over-representation of pathways impacting colonic motility (e.g. genes involved in tryptophan and serotonin degradation and mitochondrial dysfunction). Regression analysis identified a single long non-coding RNA that could predict cluster assignment with a high specificity (0.88), sensitivity (0.89) and accuracy (0.89). Comparison of gene expression profiles in the ascending colon from a subset of patients with ASD, chronic right-sided fecal loading constipation and a slow versus fast response to therapy has identified molecular mechanisms that likely contribute to this differential response following the primary therapeutic intervention (i.e. treatment for colonic inflammation with brief induction immunosuppression followed by maintenance non-steroidal anti-inflammatory therapy). Importantly, we have identified a transcript that, if validated, may provide a biomarker that can predict from the outset which patients will be slow responders who would benefit from an alternate therapeutic strategy in treating their constipation.Entities:
Mesh:
Substances:
Year: 2019 PMID: 30979947 PMCID: PMC6461625 DOI: 10.1038/s41598-019-42568-1
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Abdominal radiograph of 3 year old boy with autism and right-sided colonic fecal loading with colonic distention.
Study participant demographics.
| Slow Response | Fast Response | |
|---|---|---|
|
| 20 | 15 |
|
| ||
| Mean (SD) | 9.0 (3.81) | 5.8 (3.61) |
| Range | 3.6–15.2 | 2.1–17.9 |
|
| ||
| Male (%) | 16 (80) | 13 (87) |
| Female (%) | 4 (20) | 2 (13) |
Figure 2Flow diagram depicting data analysis scheme. Top Right: Heatmap representing all study samples. Hierarchical cluster analysis was computed using an inter-individual similarity matrix of Euclidean distances between the normalized expression values for each of the samples. This analysis resulted in two distinct clusters (as indicated). Bottom Right: Volcano plot representing the distribution of the 2992 differentially expressed genes between cluster 1 and cluster 2.
Ingenuity Pathway Analysis results.
| Pathways | p-value – range |
|---|---|
| Th1 and Th2 Activation Pathway | 1.65E-25 |
| Th2 Pathway | 1.10E-20 |
| Th1 Pathway | 1.11E-20 |
| iCOS-iCOSL Signaling in T Helper Cells | 5.45E-117 |
| Altered T Cell and B Cell Signaling | 608E-16 |
|
| |
| Hematological System Development and Function | 6.19E-14–1.80E-73 |
| Tissue Morphology | 6.04E-14–1.80E-73 |
| Lymphoid Tissue Structure and Development | 6.08E-14–1.85E-72 |
| Immune Cell Trafficking | 6.19E-14–9.05E-67 |
| Hematopoiesis | 6.08E-14–7.80E-63 |
|
| |
| Cancer | 5.72E-14–6.44E-71 |
| Organismal Injury and Abnormalities | 6.04E-14–6.44E-71 |
| Inflammatory Response | 2.58E-14–9.05E-67 |
| Dermatological Diseases and Conditions | 2.46E-14–1.75E-65 |
| Gastrointestinal Disease | 5.38E-15–2.27E-49 |
Top five over-represented biological pathways and functions from a comparison of differential gene expression (N = 2992 DETs) between cluster 1 (mostly fast responders) and cluster 2 (mostly slow responders) in right colonic tissue from children with ASD and slow response versus fast response constipation.
Top twenty canonical pathways generated in IPA wherein the majority of differentially-expressed transcripts are up-regulated in one of the two clusters.
| Up-Regulated in Chronic (Fast Response) Constipation | p-value |
|---|---|
| Th1 and Th2 Activation Pathway | 8.85E-35 |
| Th1 Pathway | 2.86E-28 |
| Th2 Pathway | 9.79E-28 |
| iCOS-iCOSL Signaling in T Helper Cells | 2.32E-22 |
| Altered T Cell and B Cell Signaling in Rheumatoid Arthritis | 5.22E-21 |
| Communication between Innate and Adaptive Immune Cells | 4.22E-20 |
| T Helper Cell Differentiation | 5.13E-19 |
| Primary Immunodeficiency Signaling | 6.65E-19 |
| CD28 Signaling in T Helper Cells | 1.75E-17 |
| Dendritic Cell Maturation | 3.31E-17 |
| T Cell Receptor Signaling | 3.27E-15 |
| Systemic Lupus Erythematosus Signaling | 1.88E-14 |
| Leukocyte Extravasation Signaling | 1.09E-13 |
| Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis | 1.17E-13 |
| Role of NFAT in Regulation of the Immune Response | 1.24E-13 |
| TREM1 Signaling | 1.36E-13 |
| B Cell Receptor Signaling | 3.71E-13 |
| PKCθ Signaling in T Lymphocytes | 4.06E-13 |
| Neuroinflammation Signaling Pathway | 1.42E-11 |
| PI3K Signaling in B Lymphocytes | 2.18E-11 |
|
| |
| Superpathway of Melatonin Degradation | 1.72E-13 |
| Melatonin Degradation I | 6.32E-12 |
| Serotonin Degradation | 1.20E-11 |
| Nicotine Degradation II | 7.20E-11 |
| Nicotine Degradation III | 8.95E-10 |
| LPS/IL-1-Mediated Inhibition of RXR Function | 9.77E-10 |
| Thyroid Hormone Metabolism II | 3.64E-09 |
| Xenobiotic Metabolism Signaling | 2.17E-08 |
| PXR/RXR Activation | 3.79E-06 |
| Glutaryl-CoA Degradation | 8.44E-05 |
| α-tocopherol Degradation | 1.09E-04 |
| Ketogenesis | 1.53E-04 |
| Valine Degradation I | 1.57E-0.4 |
| Estrogen Biosynthesis | 2.12E-04 |
| Retinol Biosynthesis | 2.48E-04 |
| Urea Cycle | 5.22E-04 |
| Isoleucine Degradation I | 6.64E-04 |
| Mitochondrial Dysfunction | 7.59E-04 |
| Dopamine Degradation | 8.02E-04 |
| Bupropion Degradation | 8.19E-04 |
Figure 3Canonical pathway network analysis. (A) Top pathways that contain a majority of upregulated genes in the fast responder group. (B) Top pathways that contain a majority of upregulated genes in the slow responder group. Blue lines indicate overlapping (shared) genes in one or more pathways. Numbers = p-value for gene representation in a given pathway from this dataset.
Figure 4Predictive ability of XXbac.B476C20.9. Using a leave-one-out approach, a single long noncoding RNA Xxbac.B476C20.9 was used to predict where samples would cluster.