| Literature DB >> 26424969 |
Tamsyn Derrick1, Chrissy h Roberts1, Anna R Last1, Sarah E Burr1, Martin J Holland1.
Abstract
Trachoma is a blinding disease usually caused by infection with Chlamydia trachomatis (Ct) serovars A, B, and C in the upper tarsal conjunctiva. Individuals in endemic regions are repeatedly infected with Ct throughout childhood. A proportion of individuals experience prolonged or severe inflammatory episodes that are known to be significant risk factors for ocular scarring in later life. Continued scarring often leads to trichiasis and in-turning of the eyelashes, which causes pain and can eventually cause blindness. The mechanisms driving the chronic immunopathology in the conjunctiva, which largely progresses in the absence of detectable Ct infection in adults, are likely to be multifactorial. Socioeconomic status, education, and behavior have been identified as contributing to the risk of scarring and inflammation. We focus on the contribution of host and pathogen genetic variation, bacterial ecology of the conjunctiva, and host epigenetic imprinting including small RNA regulation by both host and pathogen in the development of ocular pathology. Each of these factors or processes contributes to pathogenic outcomes in other inflammatory diseases and we outline their potential role in trachoma.Entities:
Mesh:
Year: 2015 PMID: 26424969 PMCID: PMC4573990 DOI: 10.1155/2015/791847
Source DB: PubMed Journal: Mediators Inflamm ISSN: 0962-9351 Impact factor: 4.711
Figure 1Images from a normal healthy eye (a–d) and from individuals with follicular trachoma (e–h), trachomatous scarring (i–l), and trichiasis and progressive scarring (m–p). (a), (e), (i), and (m) are photographs of the tarsal conjunctiva showing normal appearance (a), papillary inflammation and follicles (e), bands of trachomatous scarring (i), and extreme trichiasis and corneal opacity (m). (b), (c), (f), (g), (h), (j), (k), and (l) are in vivo confocal microscopy images of the tarsal conjunctiva at various depths (the bar represents 50 μm). A moderate number of inflammatory nuclei are present in the subepithelium of a healthy eye (b), whereas a higher number are present in trachomatous inflammation (f). Follicles can be seen in (g) and (h). The connective tissue of the healthy conjunctiva is amorphous (c), whereas successive grades of trachomatous scarring are seen as a heterogeneous clumpy appearance (j), defined tissue bands that make up <50% of the scan area (k), and defined bands that make up >50% of the scan area (l). (d) and (n–p) are histological images of tissue scarring using polarized light (original magnification ×100). In the healthy conjunctiva, collagen fibers are parallel (arrows) with the surface epithelium (d), whereas progressive disorganization of this appearance is observed in scarring (n–p). Images are kindly provided with permission from Matthew Burton and Victor Hu and are adapted from Hu et al. 2011 [11] and Hu et al. 2013 [12].
Figure 2Evidence for MMP9-IL10 epistasis in Gambians with trachomatous scarring. The protective effect of MMP9 allele (Q279R) is modulated by host genetic background at the IL10 locus such that protective effects of the G allele are lost in the presence of either of 2 minor frequency risk alleles (IL10-1082C or IL10-3575A). The interaction between these nonallelic genes (or risk genotypes) has a dominant effect over other combinations. The interaction between risk genotypes was examined by conditional likelihood ratio tests (LRT) (main effects) log p/1 − p = a + b (SNP1) + c (SNP2). Interaction terms were defined as Log p/1 − p = a + b(SNP1) + c(SNP2) + d(SNP1∗SNP2) and when significant identified statistical epistasis. This approach was applied to 651 Gambian case-control pairs of TS. The MMP9 Q279R and IL10-3575 loci showed strong evidence for statistical interaction affecting risk of TS (LRT χ 2 = 7.23, P = 0.007). Carriers of the (protective) MMP9 Q279R G allele who also had the IL10-3575A minor allele were at significantly increased risk of TS (OR = 1.83 (1.06–3.19)) when compared to subjects with the IL10-3575 T allele (common allele) (OR = 0.84 (0.69–1.02)). The IL10-1082 C minor allele in combination with the MMP9 Q279R G allele had an increased risk of TS (OR = 1.51 (1.02–2.24)) relative to IL10-1082 C in the presence of the MMP9 Q279R A allele (OR = 0.82 (0.67–1.01)) (LRT χ 2 = 7.53, P = 0.006 for the interaction between the IL10-1082 and MMP9 risk alleles). Interaction between IL10-1082 and MMP9 Q279R affects risk despite the null single SNP main effect for IL10-1082 [71]. The individually protective MMP9 Q279R G allele was therefore associated with an increased risk of scarring in the presence of IL10 risk alleles (IL10-1082C or IL10-3575A minor alleles) and a decreased risk in the presence of common IL10 (protective) alleles. Similar modelling at other loci previously investigated in this cohort (IFNγ-1616, +3234; LTA -252, +77; IkBL -63; IL-8 -251; GM-CSF2 27348, 27438) showed significant or marginally significant evidence for two-way interactions, at the genotype or allelic level, with the MMP9 Q279R SNP. Some of these SNPs are in high LD and therefore not all the hypotheses tested are independent. The existence both of LD between loci and of potential biological interdependence between loci raises methodological difficulties in correction for multiple testing. We did not attempt any correction for multiple testing: and therefore a contribution of chance to these results is difficult to exclude as we point out in the main text. Comparing main and additional two-way epistatic effects in the final model suggested that the inclusion of interaction terms improved the fit of the model to the data, so that the final best model included both main and epistatic effects. For TS this model suggested that two-way interactions of MMP9-Q279R with IFNγ-1616, IFNγ+3234, IL10-1082, IL8-251, LTA+77, LTA-252, and IkBL-63 improved the fit of the model (data courtesy of Natividad, Mabey, Holland, and Bailey).
miR predicted to regulate differentially expressed transcripts from four array datasets.
| miR functional categories | MsigDb predicted miR based on differentially regulated mRNA transcripts | |||
|---|---|---|---|---|
| (FC > 1.5 Adj. | ||||
| Active disease with | Active disease (GSE20430) | Trachomatous scarring disease with inflammation (GSE24383) | Trachomatous trichiasis with inflammation (GSE23705) | |
| Inflammation/infection |
| miR-511 |
| |
|
| miR-19a/b | |||
| miR-19a/b | miR-224 | |||
| miR-29a/b/c | ||||
|
| ||||
| EMT/fibrosis | miR-200b/c, miR-429 | miR-200b/c, miR-429 | ||
| miR-506 | miR-29a/b/c | |||
| miR-506 | ||||
| miR-520d | ||||
|
| ||||
| Cell cycle/cancer |
| miR-518a-2 | miR-128a/b |
|
| miR-124a | miR-186 |
| miR-19a/b | |
|
| miR-130a/b, miR-301 | miR-26a/b | miR-22 | |
| miR-15 family | miR-519a/b/c | miR-224 | ||
| miR-17-5p, miR-20a/b, miR-106a/b, and miR-519d | miR-25, miR-32, | |||
| miR-19a/b | miR-516-3p | |||
| miR-218 | miR-519a/b/c | |||
|
| miR-520d | |||
|
| ||||
| miR-519a/b/c | ||||
| miR-524 | ||||
| miR-9 | ||||
|
| ||||
| Other | miR-130a/b, miR-301 | miR-153 | miR-27a/b | |
| miR-516-5p | ||||
Phenotype comparisons are as follows: normal healthy (N) children aged 1–9 versus those with active trachoma (TF) and Ct infection (GSE20436); children aged 1–9 with TF (with or without Ct infection) versus N (GSE20430); N adults versus adults with trachomatous scarring and clinical inflammation (TSI) (GSE24383); and N adults versus adults with trichiasis and clinical inflammation (TTI) (GSE23705). Enriched miR are grouped into functional categories based on well-characterized roles in the literature. References show published studies that identify miR in bold as differentially expressed in chlamydial infection.