Gene-expression signatures: biomarkers toward diagnosing multiple sclerosis

Longitudinal assessment and stability of long non-coding RNA gene expression profiles measured in human peripheral whole blood collected into PAXgene blood RNA tubes

Objective

Long non-coding RNAs (lncRNAs) are emerging as novel biomarkers for a variety of chronic conditions including autoimmune disease. PAXgene Blood RNA tubes are routinely used in clinical research and molecular diagnostic development to capture RNA profiles in peripheral whole blood. While the stability of mRNA expression profiles captured using PAXgene tubes has been documented previously, no previous work has determined the stability of lncRNA expression profiles observed in PAXgene tubes stored at − 80 °C. Here we sought to determine the effects on lncRNA expression profiles following − 80 °C storage of total RNA templates, cDNA synthesized using fresh or frozen total RNA template, and the impact of freeze–thaw cycles on both total RNA and cDNA obtained from PAXgene tubes.

Results

We find that storage of whole blood in PAXgene tubes, total RNA and cDNA for up to 1 year at − 80 °C or up to ten total RNA or cDNA freeze–thaw cycles do not significantly alter lncRNA expression profiles compared to baseline. As monthly expression profiles were determined, some month to month lncRNA expression variability was observed. However, all monthly observations fell within the 95% confidence interval calculated at baseline.

Endogenous double-stranded Alu RNA elements stimulate IFN-responses in relapsing remitting multiple sclerosis

Various sensors that detect double-stranded RNA, presumably of viral origin, exist in eukaryotic cells and induce IFN-responses. Ongoing IFN-responses have also been documented in a variety of human autoimmune diseases including relapsing-remitting multiple sclerosis (RRMS) but their origins remain obscure. We find increased IFN-responses in leukocytes in relapsing-remitting multiple sclerosis at distinct stages of disease. Moreover, endogenous RNAs isolated from blood cells of these same patients recapitulate this IFN-response if transfected into naïve cells. These endogenous RNAs are double-stranded RNAs, contain Alu and Line elements and are transcribed from leukocyte transcriptional enhancers. Thus, transcribed endogenous retrotransposon elements can co-opt pattern recognition sensors to induce IFN-responses in RRMS.

Optimizing multiple sclerosis diagnosis: gene expression and genomic association

OBJECTIVE

The diagnosis of multiple sclerosis (MS) at disease onset is sometimes masqueraded by other diagnostic options resembling MS clinically or radiologically (NonMS). In the present study we utilized findings of large-scale Genome-Wide Association Studies (GWAS) to develop a blood gene expression-based classification tool to assist in diagnosis during the first demyelinating event.

METHODS

We have merged knowledge of 110 MS susceptibility genes gained from MS GWAS studies together with our experimental results of differential blood gene expression profiling between 80 MS and 31 NonMS patients. Multiple classification algorithms were applied to this cohort to construct a diagnostic classifier that correctly distinguished between MS and NonMS patients. Accuracy of the classifier was tested on an additional independent group of 146 patients including 121 MS and 25 NonMS patients.

RESULTS

We have constructed a 42 gene-transcript expression-based MS diagnostic classifier. The overall accuracy of the classifier, as tested on an independent patient population consisting of diagnostically challenging cases including NonMS patients with positive MRI findings, achieved a correct classification rate of 76.0 ± 3.5%.

INTERPRETATION

The presented diagnostic classification tool complements the existing diagnostic McDonald criteria by assisting in the accurate exclusion of other neurological diseases at presentation of the first demyelinating event suggestive of MS.

Expression of IL-33 and its epigenetic regulation in Multiple Sclerosis

Objective

We examined the expression of IL-33 as an indicator of an innate immune response in relapsing remitting MS (RRMS) and controls. We proposed a link between the expression of IL-33 and IL-33 regulated genes to histone deacetylase (HDAC) activity and in particular HDAC3, an enzyme that plays a role in the epigenetic regulation of a number genes including those which regulate inflammation.

Methods

Using TaqMan low density arrays, flow cytometry and ELIZA, expression of IL-33, and family of innate immune response genes which regulate cytokine gene expression was examined in RRMS patients and controls.

Results

Intracellular expression of IL-33 and IL-33 regulated genes are increased in patients with RRMS. In addition, following in vitro culture with TLR agonist lipopolysaccharide (LPS), there is increased induction of both IL-33 and HDAC3 in RRMS patients over that seen in controls. Also, culture of PBMC with IL-33 led to the expression of genes which overlapped with that seen in RRMS patients suggesting that the gene expression signature seen in RRMS is likely to be driven by IL-33 mediated innate immune pathways. Expression of levels of IL-33 but not IL-1 (another gene regulated by TLR agonists) is completely inhibited by Trichostatin A (TSA) establishing a closer regulation of IL-33 but not IL-1 with HDAC.

Interpretation

These results demonstrate the over expression of innate immune genes in RRMS and offer a causal link between the epigenetic regulation by HDAC and the induction of IL-33.

Using biomarkers to predict progression from clinically isolated syndrome to multiple sclerosis

Background

Detection of brain lesions disseminated in space and time by magnetic resonance imaging remains a cornerstone for the diagnosis of clinically definite multiple sclerosis. We have sought to determine if gene expression biomarkers could contribute to the clinical diagnosis of multiple sclerosis.

Methods

We employed expression levels of 30 genes in blood from 199 subjects with multiple sclerosis, 203 subjects with other neurologic disorders, and 114 healthy control subjects to train ratioscore and support vector machine algorithms. Blood samples were obtained from 46 subjects coincident with clinically isolated syndrome who progressed to clinically definite multiple sclerosis determined by conventional methods. Gene expression levels from these subjects were inputted into ratioscore and support vector machine algorithms to determine if these methods also predicted that these subjects would develop multiple sclerosis. Standard calculations of sensitivity and specificity were employed to determine accuracy of these predictions.

Results

Our results demonstrate that ratioscore and support vector machine methods employing input gene transcript levels in blood can accurately identify subjects with clinically isolated syndrome that will progress to multiple sclerosis.

Conclusions

We conclude these approaches may be useful to predict progression from clinically isolated syndrome to multiple sclerosis.

Using gene expression data to identify certain gastro-intestinal diseases

Background

Inflammatory bowel diseases, ulcerative colitis and Crohn’s disease are considered to be of autoimmune origin, but the etiology of irritable bowel syndrome remains elusive. Furthermore, classifying patients into irritable bowel syndrome and inflammatory bowel diseases can be difficult without invasive testing and holds important treatment implications. Our aim was to assess the ability of gene expression profiling in blood to differentiate among these subject groups.

Methods

Transcript levels of a total of 45 genes in blood were determined by quantitative real-time polymerase chain reaction (RT-PCR). We applied three separate analytic approaches; one utilized a scoring system derived from combinations of ratios of expression levels of two genes and two different support vector machines.

Results

All methods discriminated different subject cohorts, irritable bowel syndrome from control, inflammatory bowel disease from control, irritable bowel syndrome from inflammatory bowel disease, and ulcerative colitis from Crohn’s disease, with high degrees of sensitivity and specificity.

Conclusions

These results suggest these approaches may provide clinically useful prediction of the presence of these gastro-intestinal diseases and syndromes.

Endothelial cells and fibroblasts amplify the arthritogenic type I IFN response in murine Lyme disease and are major sources of chemokines in Borrelia burgdorferi-infected joint tissue

Localized elevation in type I IFN has been uniquely linked to the severe Lyme arthritis that develops in C3H mice infected with the spirochete Borrelia burgdorferi. In this study, the dynamic interactions that result in generation of these responses were further examined in C3H mice carrying the type I IFN receptor gene ablation, which effectively blocks all autocrine/paracrine signaling crucial to induction of downstream effectors. Reciprocal radiation chimeras between C3H and IFNAR1⁻/⁻ mice implicated both radiation-sensitive and radiation-resistant cells of the joint tissue in the proarthritic induction of type I IFN. Ex vivo analysis of cells from the naive joint revealed CD45⁺ cells residing in the tissue to be uniquely capable of initiating the type I IFN response to B. burgdorferi. Type I IFN responses were analyzed in real time by lineage sorting of cells from infected joint tissue. This demonstrated that myeloid cells, endothelial cells, and fibroblasts were responsible for propagating the robust IFN response, which peaked at day 7 postinfection and rapidly resolved. Endothelial cells and fibroblasts were the dominant sources of IFN signature transcripts in the joint tissue. Fibroblasts were also the major early source of chemokines associated with polymorphonuclear leukocyte and monocyte/macrophage infiltration, thus providing a focal point for arthritis development. These findings suggest joint-localized interactions among related and unrelated stromal, endothelial, and myeloid cell lineages that may be broadly applicable to understanding the pathogeneses of diseases associated with type I IFN signature, including systemic lupus erythematosus and some rheumatoid arthritides.