Gene expression profiles: creating new perspectives in arthritis research

Predicting tissue-specific gene expression from whole blood transcriptome

Complex diseases are mediated via transcriptional dysregulation in multiple tissues. Thus, knowing an individual's tissue-specific gene expression can provide critical information about her health. Unfortunately, for most tissues, the transcriptome cannot be obtained without invasive procedures. Could we, however, infer an individual's tissue-specific expression from her whole blood transcriptome? Here, we rigorously address this question. We find that an individual's whole blood transcriptome can significantly predict tissue-specific expression levels for ~60% of the genes on average across 32 tissues, with up to 81% of the genes in skeletal muscle. The tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including hypertension and type 2 diabetes, substantially surpassing the blood transcriptome. The code for tissue-specific gene expression prediction, TEEBoT, is provided, enabling others to study its potential translational value in other indications.

Use of DNA microarray analysis in diagnosis of bacterial and fungal endophthalmitis

Background

To examine the utility of DNA microarray analysis for identifying causative microorganisms in endophthalmitis.

Methods

Thirteen samples of vitreous fluid (VF) were obtained from 13 patients during vitrectomy. Vitreous fluids from three patients with suspected endophthalmitis and ten controls without infection were subjected to testing for the presence of bacteria and fungi in culture tests, polymerase chain reaction (PCR) analysis, and DNA microarray analysis.

Results

No control sample was positive for bacteria or fungi in the culture test, PCR, or microarray analysis. Specimens from two patients (Cases 1 and 2) with suspected endophthalmitis were positive for bacteria in PCR, and a specimen from one patient (Case 3) was positive for fungi in PCR. Klebsiella pneumonia (Case 1), Streptococcus agalactiae (Case 2), and Candida parapsilosis (Case 3) in the PCR-positive specimens were identified by DNA microarray analysis within 24 hours. Culture results were also positive for K. pneumonia in Case 1, S. agalactiae in Case 2, and C. parapsilosis in Case 3, but required 3 to 4 days to obtain.

Conclusions

Microarray analysis is complementary to routine cultures for identifying causative microorganisms and is likely to be a useful tool in patients with suspected endophthalmitis who require rapid diagnosis and early antibiotic treatment.

Transcriptome profiling of whole blood cells identifies PLEK2 and C1QB in human melanoma

Background

Developing analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a “nucleic acid-rich” and “inflammatory cell-rich” information reservoir and represents systemic processes altered by the presence of cancer cells.

Methodology/Principal Findings

We conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45⁻ and CD45⁺ populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively.

Conclusions/Significance

The current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45⁻ subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease.

Transcriptional profiling and pathway analysis of monosodium iodoacetate-induced experimental osteoarthritis in rats: relevance to human disease

OBJECTIVE

The objective of this study was to characterize the rat monosodium iodoacetate (MIA)-induced model for osteoarthritis (OA) and determine the translatability of this model to human disease. This was accomplished through pathway, network and system level comparisons of transcriptional profiles generated from animal and human disease cartilage.

METHODS

An OA phenotype was induced in rat femorotibial joints following a single injection of 200mug MIA per knee joint for a period of 2 or 4 weeks. Lesion formation in the rat joints was confirmed by histology. Gene expression changes were measured using the Agilent rat whole genome microarrays. Cartilage was harvested from human knees and gene expression changes were measured using the Agilent human arrays.

RESULTS

One thousand nine hundred and forty-three oligos were differentially expressed in the MIA model, of these, approximately two-thirds were up-regulated. In contrast, of the 2130 differentially expressed oligos in human disease tissue, approximately two-thirds were down-regulated. This dramatic difference was observed throughout each level of the comparison. The total overlap of genes modulated in the same direction between rat and human was less than 4%. Matrix degradation and inflammatory genes were differentially regulated to a much greater extent in MIA than human disease tissue.

CONCLUSION

This study demonstrated, through multiple levels of analysis, that little transcriptional similarity exists between rat MIA and human OA derived cartilage. As disease modulatory activities for potential therapeutic agents often do not translate from animal models to human disease, this and like studies may provide a basis for understanding the discrepancies.

Genetic influences on joint contractures secondary to immobilization

The primary research question of this study queries whether, beyond environmental conditions, genetic factors affect the development of joint contractures. We hypothesized that intrinsic genetic factors influence the severity of joint contractures developing secondary to joint immobilization. Forty rats from four inbred rat strains had one leg immobilized in knee flexion for 4 weeks. The contracture was measured mechanically as the lack of range of motion to a standardized torque. Using the contralateral leg as a control, the average severity of the contracture could be calculated and compared between strains. All immobilized legs presented knee contractures after 4 weeks of immobilization. Two strains (Dark Agouti and Fisher 344) showed a larger mean knee contracture than those of the two other rat strains (Augustus Copenhagen Irish and Brown Norway). Environmental factors, such as immobility, are usually identified as a cause of a joint contracture. These results demonstrate that, in addition to mechanical factors in the environment of a joint, intrinsic genetic factors participate in the process leading to joint contracture. This demonstration has important consequences for directing future research and may lead to interventions to help patients at risk of developing joint contractures.

Molecular targets in immune-mediated diseases: focus on rheumatoid arthritis

There are a large number of diseases involving inappropriate activation of the immune system. This review focuses on one such disease, rheumatoid arthritis (RA). Over recent years there has been a dramatic shift in the treatment of RA, in which biological agents, such as monoclonal antibodies and immuno-fusion proteins, have offered the potential to enhance or replace conventional immunosuppressive therapies. This review covers some of the novel biological molecules currently under investigation as potential therapeutic targets in RA. In addition, it covers the genomic and proteomic strategies being used to identify potential new molecular targets for future therapies. Selectively blocking the immune response, in a combination approach blocking not only inflammation but also the adaptive memory response and tissue destruction, holds great promise for the treatment of RA and many other immune-mediated diseases.

Gene expression profiling in murine autoimmune arthritis during the initiation and progression of joint inflammation

We present here an extensive study of differential gene expression in the initiation, acute and chronic phases of murine autoimmune arthritis with the use of high-density oligonucleotide arrays interrogating the entire mouse genome. Arthritis was induced in severe combined immunodeficient mice by using adoptive transfer of lymphocytes from proteoglycan-immunized arthritic BALB/c mice. In this unique system only proteoglycan-specific lymphocytes are transferred from arthritic mice into syngeneic immunodeficient recipients that lack adaptive immunity but have intact innate immunity on an identical (BALB/c) genetic background.

Differential gene expression in response to donor lymphocytes that migrated into the joint can therefore be monitored in a precisely timed manner, even before the onset of inflammation. The initiation phase of adoptively transferred disease (several days before the onset of joint swelling) was characterized by differential expression of 37 genes, mostly related to chemokines, interferon-γ and tumor necrosis factor-α signaling, and T cell functions. These were designated early arthritis 'signature' genes because they could distinguish between the naive and the pre-arthritic state. Acute joint inflammation was characterized by at least twofold overexpression of 256 genes and the downregulation of 21 genes, whereas in chronic arthritis a total of 418 genes with an equal proportion of upregulated and downregulated transcripts were expressed differentially.

Hierarchical clustering and functional classification of inflammation-related and arthritis-related genes indicated that the most common biological activities were represented by genes encoding interleukins, chemokine receptors and ligands, and by those involved in antigen recognition and processing.

Molecular Genetics of Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (AD) is a complex and multifactorial disease with the possible involvement of several genes. Apolipoprotein E (APOE), especially the APOE*4 allele, has been established as a strong susceptibility marker that accounts for nearly 30% of the risk in late-onset AD. However, as the APOE*4 allele is neither necessary nor sufficient for the development of AD, it emphasizes the involvement of other genetic and/or environmental factors which, alone or in conjunction with APOE*4, can modify the risk of AD. Recently, genome-wide linkage or linkage disequilibrium studies on late-onset AD have provided informative data for the existence of multiple putative genes for AD on several chromosomes, with the strongest evidence on chromosomes 12, 10, 9 and 6. This paper attempts to review the current progress on the identification of additional genetic loci for late-onset AD.

Perspectives and limitations of gene expression profiling in rheumatology: new molecular strategies

The deciphering of the sequence of the human genome has raised the expectation of unravelling the specific role of each gene in physiology and pathology. High-throughput technologies for gene expression profiling provide the first practical basis for applying this information. In rheumatology, with its many diseases of unknown pathogenesis and puzzling inflammatory aspects, these advances appear to promise a significant advance towards the identification of leading mechanisms of pathology. Expression patterns reflect the complexity of the molecular processes and are expected to provide the molecular basis for specific diagnosis, therapeutic stratification, long-term monitoring and prognostic evaluation. Identification of the molecular networks will help in the discovery of appropriate drug targets, and permit focusing on the most effective and least toxic compounds. Current limitations in screening technologies, experimental strategies and bioinformatic interpretation will shortly be overcome by the rapid development in this field. However, gene expression profiling, by its nature, will not provide biochemical information on functional activities of proteins and might only in part reflect underlying genetic dysfunction. Genomic and proteomic technologies will therefore be complementary in their scientific and clinical application.

Drug-induced and toxic myopathies

Drug-induced myopathies and, more rarely, rhabdomyolysis, are a common biological and clinical setting for clinical rheumatologists. The focus of this chapter is to review (i) the clinical presentation and management of these adverse drug reactions (ADR) according to pain and associated neurological symptoms, (ii) the common drugs prescribed by rheumatologists which may induce reactions such as ADR, with special reference to new drugs, (iii) the pathological classification associated with specific patterns, and (iv) the risk factors leading to myotoxicity (including genetic predisposition). Specific features to be reviewed include macrophage myofasciitis and biological agents of major importance when considering terrorist attacks with biological weapons. When diagnosis is suspected, discontinuation of the putative drug(s) is mandatory and should be carefully monitored.

Genomics of osteoarthritis

PURPOSE OF REVIEW

This review addresses the progress in three major fields of "genomics of osteoarthritis" over the past year: genetic alterations thought to be important for the initiation and progression of osteoarthritis, differential gene expression analysis, and functional genomics of osteoarthritis.

RECENT FINDINGS

Distinct genetic risk factors may predispose different joint sites to osteoarthritis, and although clear loci for susceptibility genes for common osteoarthritis have yet to emerge from the epidemiological studies, new approaches are narrowing down known loci. The search for specific genes using cDNA array technology has further demonstrated its potential in arthritis research as a powerful tool that could further provide biological insights into disease mechanisms, osteoarthritis polymorphic subtypes, the molecular validation of animal models, and the monitoring of drug activity on gene expression levels. Gene expression analysis has further characterized the striking shift in the gene expression pattern during "dedifferentiation" of chondrocytes in vitro as well as added depth to the phenotype of differentiated versus undifferentiated mesenchymal stem cells. Several new molecules potentially relevant to the disease process were identified, among them beta2-microglobulin (B2M), clusterin, and chitinase-like molecule 2.

SUMMARY

Functional genomic approaches will in the future allow to complement traditional biochemistry and molecular biology. Although there are limitations to cDNA array technology, "molecular portraits" of osteoarthritic chondrocytes in vivo and in vitro can be produced to analyze whole or large biologic systems rather than just single aspects of it. This will stimulate the testing of new markers, which are needed for the diagnosis and monitoring of osteoarthritis.

A new tool for rheumatology: large-scale analysis of gene expression

Large-scale analysis of gene expression with cDNA arrays is spreading over many biological fields, including rheumatology. In this report, we wish to explain the principle and main advantages of this tool in the context of our discipline. Until 1995, analysis of gene expression was conducted for a few genes at a time but DNA chips now allow one to monitor the expression of thousands of genes in a single experiment and analyze the transcriptome, i.e. the whole of the transcripts in a given cell or tissue. Whatever the platform used (macro- or microarrays, oligo-chips), this technology rests upon the hybridization of i) a set of cDNA clones tethered to a solid support (nylon or glass) as probes, and ii) labelled cDNAs that are reverse-transcribed from bulk mRNAs extracted from a cell or tissue sample as a target. The end result is information on the relative abundance of every mRNA between two or more samples. The transcriptome analysis has two main objectives in rheumatology: i) identifying a gene expression profile that is a hallmark of a pathology and using it for a diagnostic or prognostic purpose, and ii) gathering genes with similar changes of expression, which allows one to specify the identity of novel proteins involved in a well-known intracellular cascade of regulation or even to identify new cascades.

Functional genomics of osteoarthritis

Functional genomics is a challenging new way to address a complex disease like osteoarthritis on a molecular level. Despite osteoarthritis being ultimately a biochemical problem, mainly characterized by an imbalanced cartilage matrix turnover, a deeper understanding of molecular events within the tissue cells (i.e., the chondrocytes) will provide not only a better understanding of pathogenetic mechanisms but also new diagnostic markers and cellular targets for therapeutic intervention. This innovative technology represents a challenging approach complementing (not replacing) classical research in previously described and new disease-relevant genes: large-scale functional genomics will open up new areas of so far unrecognized molecular networks. This will include as yet unidentified players in the anabolic-catabolic balance of matrix turnover of articular cartilage as well as disease-relevant intracellular signaling cascades so far hardly investigated in articular chondrocytes. However, care must be taken not to over or misinterpret results and some major challenges must be overcome in order to properly utilize the potential of this technology in the field of osteoarthritis.