Immune recognition of self nucleic acids driven by endogenous antimicrobial peptides: role in autoimmunity

Innate immune recognition of extracellular host-derived self-DNA and self-RNA is prevented by endosomal seclusion of the Toll-like receptors (TLRs) in the dendritic cells (DCs). However, in psoriasis plasmacytoid dendritic cells have been found to be able to sense self-DNA molecules in complex with the endogenous cationic antimicrobial peptide LL37, which are internalized into the endosomal compartments and thus can access TLR9. We investigated whether this endogenous peptide can also interact with extracellular self-RNA and lead to DC activation. We found that LL37 binds self-RNA as well as self-DNA going into an electrostatic interaction; forms micro-aggregates of nano-scale particles protected from enzymatic degradation and transport it into the endosomal compartments of both plasmacytoid and myeloid dendritic cells. In the plasmacytoid DCs, the self-RNA-LL37 complexes activate TLR7 and like the self-DNA-LL37 complexes, trigger the production of IFN-α in the absence of induction of maturation or production of IL-6 and TNF-α. In contrast to the self-DNA-LL37 complexes, the self-RNA-LL37 complexes are also internalized into the endosomal compartments of myeloid dendritic cells and trigger activation through TLR8, leading to the production of TNF-α and IL-6, and the maturation of the myeloid DCs. Furthermore, we found that these self nucleic acid-LL37 complexes can be found in vivo in the skin lesions of the cutaneous autoimmune disease psoriasis, where they are associated with mature mDCs in situ. On the other hand, in the systemic autoimmune disease systemic lupus erythematosus, self-DNA-LL37 complexes were found to be a constituent of the circulating immune complexes isolated from patient sera. This interaction between the endogenous peptide with the self nucleic acid molecules present in the immune complexes was found to be electrostatic and it confers resistance to enzymatic degradation of the nucleic acid molecules in the immune complexes. Moreover, autoantibodies to these endogenous peptides were found to trigger neutrophil activation and release of neutrophil extracellular traps composed of DNA, which are potential sources of the self nucleic acid-LL37 complexes present in SLE immune complexes. Our results demonstrate that the cationic antimicrobial peptide LL37 drives the innate immune recognition of self nucleic acid molecules through toll-like receptors in human dendritic cells, thus elucidating a pathway for innate sensing of host cell death. This pathway of autoreactivity was found to be pathologically relevant in human autoimmune diseases psoriasis and SLE, and thus this study provides new insights into the mechanisms autoimmune diseases.

Platelet-activating factor is crucial in psoralen and ultraviolet A-induced immune suppression, inflammation, and apoptosis.

Psoralen plus UVA (PUVA) is used as a very effective treatment modality for various diseases, including psoriasis and cutaneous T-cell lymphoma. PUVA-induced immune suppression and/or apoptosis are thought to be responsible for the therapeutic action. However, the molecular mechanisms by which PUVA acts are not well understood. We have previously identified platelet-activating factor (PAF), a potent phospholipid mediator, as a crucial substance triggering ultraviolet B radiation-induced immune suppression. In this study, we used PAF receptor knockout mice, a selective PAF receptor antagonist, a COX-2 inhibitor (presumably blocking downstream effects of PAF), and PAF-like molecules to test the role of PAF receptor binding in PUVA treatment. We found that activation of the PAF pathway is crucial for PUVA-induced immune suppression (as measured by suppression of delayed type hypersensitivity to Candida albicans) and that it plays a role in skin inflammation and apoptosis. Downstream of PAF, interleukin-10 was involved in PUVA-induced immune suppression but not inflammation. Better understanding of PUVA's mechanisms may offer the opportunity to dissect the therapeutic from the detrimental (ie, carcinogenic) effects and/or to develop new drugs (eg, using the PAF pathway) that act like PUVA but have fewer side effects.

PLASMACYTOID DENDRITIC CELLS SENSE SKIN INJURY AND PROMOTE WOUND HEALING THROUGH TYPE I INTERFERONS

Plasmacytoid dendritic cells (pDCs) are a rare population of circulating cells, which selectively express intracellular Toll-like receptors (TLR)-7 and TLR-9 and have the capacity to produce large amounts of type I IFNs (IFN-a/b) in response to viruses or host derived nucleic acid containing complexes. pDCs are normally absent in skin but accumulate in the skin of psoriasis patients where their chronic activation to produce IFN-a/b drives the disease formation. Whether pDCs and their activation to produce IFN-a/b play a functional role in healthy skin is unknown. Here we show that pDCs are rapidly and transiently recruited into healthy human and mouse skin upon epidermal injury. Infiltrating pDCs were found to sense nucleic acids in wounded skin via TLRs, leading to the production of IFN-a/b. The production of IFN-a/b was paralleled by a short lived expression of cathelicidins, which form complexes with extracellular nucleic acids and activated pDCs to produce IFN-a/b in vitro. In vivo, cathelicidins were sufficient but not necessary for the induction of IFN-a/b in wounded skin, suggesting redundancy of this pathway. Depletion of pDCs or inhibition of IFN-a/bR signaling significantly impaired the inflammatory response and delayed re-epithelialization of skin wounds. Thus we uncover a novel role of pDCs in sensing skin injury via TLR mediated recognition of nucleic acids and demonstrate their involvement in the early inflammatory process and wound healing response through the production of IFN-a/b.

Immunology and HIV expression in skin, in vitro, and in response to ultraviolet light

HIV can enter the body through Langerhans cells, dendritic cells, and macrophages in skin mucosa, and spreads by lysis or by syncytia. Since UVL induces of HIV-LTR in transgenic mice mid in cell lines in vitro, we hypothesized that UVB may affect HIV in people and may affect HIV in T cells in relation to dose, apoptosis, and cytokine expression. To determine whether HIV is induced by UVL in humans, a clinical study of HIV+ patients with psoriasis or pruritus was conducted during six weeks of UVB phototherapy, Controls were HIV-psoriasis patients receiving UVB and HIV+ KS subjects without UVB.Blood and skin biopsy specimens were collected at baseline, weeks 2 and 6, and 4 weeks after UVL. AIDS-related skin diseases showed unique cytokine profiles in skin and serum at baseline. In patients and controls on phototherapy, we observed the following: (1) CD4+ and CD8+ T cell numbers are not significantly altered during phototherapy, (2) p24 antigen levels, and also HIV plasma levels increase in patients not on antiviral therapy, (3) HIV-RNA levels in serum or plasma. (viral load) can either increase or decrease depending on the patient's initial viral load, presence of antivirals, and skin type, (4) HIV-RNA levels in the periphery are inversely correlated to serum IL-10 and (5) HIV+ cell in skin increase after UVL at 2 weeks by RT-PCR in situ hybridization mid we negatively correlated with peripheral load. To understand the mechanisms of UVB mediated HIV transcription, we treated Jurkat T cell lines stably transfected with an HIV-LTR-luciferase plasmid only or additionally with tat-SV-40 early promoter with UVB (2 J/m2 to 200 J/m2), 50 to 200 ng/ml rhIL-10, and 10 μg/ml PHA as control. HIV promoter activity was measured by luciferase normalized to protein. Time points up to 72 hours were analyzed for HIV-LTR activation. HIV-LTR activation had the following properties: (1) requires the presence of Tat, (2) occurs at 24 hours, and (3) is UVB dose dependent. Changes in viability by MTS (3-(4,5-dimethyhhiazol-2-y1)-5-(3-carboxymethoxyphonyl)-2-(4-sulfophenyl)-2H-tetrazolium) mixed with PMS (phenazine methosulfate) solution and apoptosis by propidium iodide and annexin V using flow cytometry (FC) were seen in irradiated Jurkat cells. We determined that (1) rhIL-10 moderately decreased HIV-LTR activation if given before radiation and greatly decreases it when given after UVB, (2) HIV-LTR activation was low at doses of greater than 70 J/m2, compared to activation at 50 J/m2. (Abstract shortened by UMI.)^

Molecular mechanism of PUVA-induced apoptosis in mouse epidermal cells

A combination of psoralens and ultraviolet-A radiation referred to as PUVA, is widely used in the treatment of psoriasis. PUVA therapy is highly effective in killing hyperproliferative cells, but its mechanism of action has not been fully elucidated. Psoralen binds to DNA, and upon photoactivation by UVA, it forms monofunctional adducts and interstrand cross-links. PUVA treatment has been shown to be mutagenic and to produce tumors in animals. In addition, epidemiological studies have reported a 10 to 15 percent increased risk of developing squamous cell carcinoma in individuals treated chronically with PUVA. However, it remains a treatment for skin disorders such as psoriasis because its benefits outweigh its risks. The widespread use of PUVA therapy and its associated cancer risk requires us to understand the molecular mechanisms by which PUVA induces cell death. Immortalized JB6 mouse epidermal cells, p53−/− mice, and Fas Ligand−/− (gld) mice were used to investigate the molecular mechanism by which PUVA kills cells. Treatment of JB6 cells with 10 μg/ml 8-methoxypsoralen followed by irradiation with 20 kJ/m2 UVA resulted in cell death. The cells exhibited morphological and biochemical characteristics of apoptosis such as chromatin condensation, DNA ladder formation, and TUNEL-positivity. PUVA treatment stabilized and phosphorylated p53 leading to its activation, as measured by nuclear localization and induction of p21Waf/Cip1, a transcriptional target of p53. Subsequent in vivo studies revealed that there was statistically significantly less apoptosis in p53 −/− mice than in p53+/+ mice at 72 hours after PUVA. In addition, immunohistochemical analysis revealed more Fas and FasL expression in p53+/+ mice than in p53−/− mice, suggesting that p53 is required to transcriptionally activate Fas, which in turn causes the cells to undergo apoptosis. Studies with gld mice confirmed a role for Fas/FasL interactions in PUVA-induced apoptosis. There was statistically significantly less apoptosis in gld mice compared with wild-type mice 24, 48, and 72 hours after PUVA. These results demonstrate that PUVA-induced apoptosis in mouse epidermal cells requires p53 and Fas/FasL interactions. These findings may be important for designing effective treatments for diseases such as psoriasis without increasing the patient's risk for skin cancer. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Involvement of {\it p53\/} in PUVA-induced skin cancers

A combination of psoralen and ultraviolet-A radiation, commonly referred to as "PUVA," is widely used in the treatment of psoriasis. However, PUVA treatment increases the risk of developing skin cancer in psoriasis patients and induces skin cancer in mice. It is, however unknown whether the increased incidence of skin cancer in PUVA treated psoriasis patients is due to the carcinogenic effects of PUVA therapy or due to an indirect effect such as immunosuppression, which can permit the growth of tumors induced by UVB radiation. In this study, we used the p53 tumor suppressor gene as a molecular marker to determine whether PUVA-induced mouse skin cancers contain unique mutations in p53 that are different from UV-induced mutations, and if so, determine whether skin cancers from PUVA treated patients have PUVA-type or UV-type p53 mutations. Since the DNA lesions induced by PUVA are quite different from those induced by UV, we hypothesize that p53 mutations induced by PUVA may also be different from those induced by UV.^ Analysis of PUVA-induced murine skin cancers for p53 mutations revealed that 14 of 15 (93%) missense mutations detected in these cancers were localized at 5$\sp\prime$-TA/5$\sp\prime$-TAT sites, potential sites of psoralen photoadditions. Mutations at these sequences are exceedingly rare in UV-induced murine skin cancers. In addition, PUVA-induced murine skin cancers did not contain UV signature (C $\to$ T or CC $\to$ TT transitions) mutations in p53. These results suggest that PUVA induces unique mutations in p53 that can be distinguished from those induced by UV.^ Next we determined whether SCCs arising in PUVA treated psoriasis patients have PUVA-type or UV-type p53 mutations. The results indicated that 16 of 25 (64%) missense p53 mutations detected in SCCs from PUVA treated patients were located at 5$\sp\prime$-TG, 5$\sp\prime$-TA and 5$\sp\prime$-TT sites, putative sites of psoralen photobinding. Interestingly, about 32% of p53 mutations detected in SCCs from PUVA treated patients had the UV signature. Taken together these results suggest that both PUVA and UVB play a role in the development of SCCs in psoriasis patients undergoing PUVA therapy. ^