Thursday 28 November 2013

ISSS Abstract: Application of probabilistic functional integrated network analysis to the study of autoimmunity and primary Sjögren's Syndrome

Katherine James, Jennifer Hallinan, Anil Wipat, Wan-Fai Ng
Objectives: The majority of experimental datasets can be represented as networks of parts and interactions. A network representation allows biological data to be represented in a manner that is both tractable for human visual study and computationally amenable. One of the most powerful approaches to the integration of heterogeneous data is the use of probabilistic functional integrated networks (PFINs), since these networks have statistical weights that indicate the level of confidence in the evidence for each interaction. The confidence weights allow the use of a variety of statistical algorithms that take these weightings into account. This study aims to integrate an immune-specific PFIN from a number of relevant experimental datasets and apply it to the study of primary Sjögren's Syndrome (pSS) and related diseases.
Methods: Functional interaction data were sourced from the BioGRID and InnateDB resources. Datasets were confidence scored using a metabolic pathway Gold Standard dataset derived from the BioSystems Database. The confidence scores were integrated for each individual interaction using a weighted sum. The proteins of the network were then annotated using Gene Ontology biological process terms. Finally, the network was filtered to produce a sub-network of immune proteins and their high confidence interaction partners. The final network was assessed for its ability to predict known autoimmune disease-related proteins before being applied to the prediction of novel pSS-associated proteins and to the comparison of autoimmune diseases using a variety of network analysis techniques.
Results: A probabilistic functional integrated network of immunity was produced. The core immune PFIN contained ˜1700 proteins which were involved in >10,000 interactions. Clustering of the network based on interaction confidence revealed distinct patterns of interaction between pSS-associated proteins and several biological processes, in particular the stress responses. In addition, a ranked list of candidate pSS-associated genes was produced.
Conclusion: Probabilistic network analysis is a powerful approach to data integration and the study of human disease. The immune PFIN generated by this work provides a valuable resource for the future study of pSS and its comparison with other autoimmune diseases.

ISSS Abstract: The United Kingdom Primary Sjögren's Syndrome Registry (UKPSSR), a valuable resource for future pSS research

Katherine James, Sheryl Mitchell, Bridget Griffiths, Simon Bowman, Wan-Fai Ng and the UKPSSR Study Group
Objectives: Primary Sjögren's Syndrome (pSS) is the second most common systemic autoimmune disease after rheumatoid arthritis. However, the mechanisms of pSS pathogenesis remain poorly understood. The United Kingdom Primary Sjögren's Syndrome Registry (UKPSSR) aims to facilitate research and improve our understanding of pSS by providing a large cohort of clinically well-characterised pSS patients and matched healthy controls. The project is an initiative of the United Kingdom Sjögren's Interest Group (UKSIG) and is funded by the Medical Research Council.
Methods: PSS patients were recruited from 30 centres across the UK. Extensive subjective and objective clinical data were collected for all patients including demographics, comorbidity, biopsy status, Schirmer's test value and treatment history. Disease activity (ESSDAI, SCAI, SSDAI) and disease damage (SDI, SSDDI) scores were calculated for all patients in the cohort. In addition, patient-reported outcomes were calculated for symptom assessment (PROFAD-SSI, ESSPRI, Epworth sleepiness scale, OGS), quality of life (EQ-5D, SF-36), and, anxiety and depression (HADS). An optional cardiovascular risk assessment was carried out for a subset of the patients. Simultaneously, age-, sex- and ethnicity-matched healthy controls were recruited. Finally, blood samples were bio-banked for all the patients and controls of the cohort.
Results: The UKPSSR is a national cohort and research biobank of approximately 700 clinically well-characterised pSS patients and around 350 matched healthy controls.
Conclusion: The UKPSSR cohort provides a resource to enhance our understanding of pSS through facilitating high-quality clinical and academic research. It is hoped that the UKPSSR will serve as a foundation for the formation of a more extensive collaborative research network for pSS.

Wednesday 27 November 2013

ISSS Abstract: Proteomic analysis of pooled blood serum samples to detect symptom-specific changes in primary Sjögren's Syndrome patients

Katherine James, Simon J Cockell, Colin S Gillespie, Anil Wipat, Jennifer Hallinan, Benedikt M Kessler, Roman Fischer, Simon J Bowman, Bridget Griffiths & The UKPSSR Study Group
Objectives: Primary Sjögren's Syndrome (pSS) is a chronic autoimmune disease characterised by a range of symptoms including dryness, fatigue, depression, anxiety, pain and an increased risk of lymphoma. Patient populations are heterogeneous in their symptoms, making the accurate identification of pSS biomarkers non-trivial. This study aims to identify symptom-specific changes in protein abundance using serum samples from the UK Primary Sjögren's Syndrome Registry (UKPSSR), a cohort of clinically well-characterised pSS patients and healthy controls.
Methods: Patients were chosen from the UKPSSR database and grouped based on their levels of dryness, fatigue, depression, anxiety, and pain. Serum samples from each subject group were pooled and analysed by LC-MS/MS analysis using a Thermo LTQ Orbitrap Velos. Bioinformatic analyses and statistical modelling were then used to characterise the proteins and identify relationships between protein abundance and symptom levels.
Results: A total of 107 proteins were found to have significant changes in abundance between patient groups (ANOVA p>0.05, based on analytical duplicates). The majority of these proteins were immunoglobulins and components of the complement and coagulation cascades. Statistical modelling indicated that several of these abundance changes correlated with symptom levels. In particular, decreases in immunoglobulin chain regions are associated with the high fatigue and high pain groups, while slight decreases in complement components C1R and C4A were associated with dryness.
Conclusions: Differences in blood serum abundance of several proteins can be detected between groups of pSS patients with heterogeneous symptom profiles. These observations suggest that specific proteins may be biomarkers for the individual symptoms of pSS. Future analysis on a patient by patient basis could potentially reveal symptom-specific bio-fingerprints for individual symptom profiles.

ISSS Abstract: Integration of gene expression data with functional interaction and annotation data reveals patterns of connection between pSS-associated genes and the cellular processes in which they are involved

Katherine James, Jessica R Tarn, Shereen Al-Ali, Jennifer Hallinan, David A Young, Wan-Fai Ng
Objectives: There is considerable discordance in data from different gene expression studies of primary Sjögren's Syndrome (pSS). Combining these data with other types of information, such as functional interactions and annotation data, can provide a more complete view of the cell in order to identify the key genes and biological pathways that are involved in the disease process of pSS.
Methods: In this study, a list of genes, found to be differentially expressed between pSS patients and controls in four large-scale microarray studies, was derived from the literature. The enrichments of Gene Ontology (GO) biological process annotations for this list were calculated in order to identify those processes that may be involved in pSS pathogenesis.
BioGRID is a comprehensive and highly-curated resource for functional association data generated by multiple experimental techniques. Using BioGRID data, a functional interaction network was generated in which nodes represented genes or gene products, and edges represented any type of BioGRID interaction between the nodes. The network was visualised using the Cytoscape visualisation platform and further annotated based on the Gene Ontology enrichment results. Finally, the network was filtered to produce sub-networks of pSS-associated genes.
Results: Following filtering, a total of 99 of the pSS-associated genes were involved in 111 interactions in the sub-network, the majority of which were connected in one component of 88 genes. All four gene expression datasets were represented within this connected component. Several tight clusters between genes annotated to the processes "innate immune response", "multi-organism process", "response to virus" and "response to stress" were observed in the integrated network. The sub-network also revealed patterns of interaction between these clusters and the pSS-associated genes. In addition, a large number of the pSS-associated genes were found to be annotated to these GO biological processes.
Conclusion: Gene enrichment and network analyses of the pSS-associated genes suggest that the innate immune responses, multi-organism processes, and the responses to virus and to stress are likely to be involved in pSS pathogenesis. Integration of multiple types of data in this manner can aid in the interpretation of results since combining diverse data sources reveals global properties not evident from a single data source. Future studies may benefit from incorporating additional detailed clinical data during the analysis of expression data in order to elucidate the relationship between gene expression and clinical phenotype.

Thursday 21 November 2013

ISSS Abstract: Effects of globin mRNA on whole blood gene expression signature in primary Sjögren’s syndrome

Al-Ali S, Cockell S, Tarn JR, James K, Young DA, the UKPSSR study group, Griffiths B, Bowman S, Ng WF

Objectives : Gene expression profiling using peripheral whole blood is a useful approach to identify biomarkers in primary Sjögren's syndrome (PSS). However, using whole blood comes with challenges as a result of the presence of globin mRNA, which represent approximately 70% of the total RNA, potentially reducing the accuracy and sensitivity of microarray analysis. The aim of this study was to evaluate the effect of globin mRNA on whole blood gene expression profiling in PSS .

Methods: Twenty-four peripheral whole blood samples from PSS patients and healthy controls (HC) were used (PSS=12, HC=12) , RNA was extracted according to the PAXgene Blood RNA kit protocol, followed by purification and concentration using the RNeasy MiniElute kit. For each sample, half of the RNA underwent a globin mRNA removal step using the GLOBINclear kit (the "globin-clear group") with the remaining half representing the "globin-present group". The efficiency of globin mRNA clearance was assessed by the ratio of real-time RT-PCR of β-globin mRNA between paired "globin-present" and "globin-clear" samples. Illumina microarrays were performed for all samples and the data analyzed using Genespring GX (Agilent).

Results:  b-globin gene expression in 'globin-clear' samples was markedly reduced compared the paired 'globin-present' samples (fold change=139-555) indicating efficient removal of globin mRNA. Consistently, an RNA quality check of the globin-clear samples using a Bioanalyser confirmed lack of a sharp peak of 700 bp which represent the globin mRNA. The Probe intensity signals of the microarray were higher and the quality of the microarray data improved in the 'globin-clear' group. Independent analysis of the 'globin-clear' and the 'globin-present' groups identified 15995 versus 15173 transcripts/entities detectably expressed (1.2-fold p>0.05) between PSS and healthy controls respectively, suggestive of an improvement in the sensitivity of the data after globin-removal. When focussing on those most highly differentially expressed genes (based on relative fold changes), there was significant concurrence between the two methods. Despite the small sample size, the differentially expressed genes identified in this study were similar to a previous report.

Conclusion: Removal of globin mRNA enhanced the quality of the samples and the microarray intensity as well as enhance sensitivity, although there were considerable overlap between the differentially expressed genes identified regardless of whether globin mRNA was removed especially for the genes with high relative levels of expression between PSS and controls.

Friday 15 November 2013

ISSS Abstract: Whole blood micro RNA signature for primary Sjögren’s syndrome-related lymphoma

Tarn JR, Cockell S, Gillespie C, Al-Ali S, James K, the UK primary Sjögren's syndrome registry, Griffiths B, Bowman S, Young DA, Ng WF

 Background: Micro RNAs (miRNAs) are 18-25nt non-coding RNAs that bind target/complementary sequences within the 3'UTR of RNA molecules steering them towards degradation or translational repression, and play a key role in the regulation of gene expression.  Better understanding of the expression pattern of miRNAs in diseases may improve our understanding of the biological basis of the disease and identify potential biomarkers. The role of miRNAs in primary Sjögren's syndrome (PSS) and PSS-related lymphoma remains poorly understood. The aim of this project is to identify a miRNA signature for PSS-related lymphoma.

 Methods: We profiled the expression of miRNAs in whole blood (PaxGene) total RNA preparations using the Exiqon miRCURY LNA array which encompasses >1400 miRNAs and other small non-coding RNAs. A discovery cohort comprised of 36 samples (12 PSS patients with lymphoma, 12 PSS patients without lymphoma, 12 healthy controls) were used in the initial analysis. We also explored different normalisation strategies and developed an approach which we considered most appropriate for analysing these data. Real-Time PCR was used to validate the most highly differentially expressed miRNAs between groups. A miRNA signature for PSS-related lymphoma was identified using cluster analysis followed by validation with a second independent cohort of 36 patients and controls.

 Results: The initial miRNA array profiling revealed a clear clustering of the 3 subject groups. Between the 'High Function' and 'Lymphoma' patient groups, 44 miRNAs were found to be differentially expressed. The differential expressions of these miRNA were validated by RT-PCR in 3 out of 9 miRNAs with the highest fold-changes between the two groups. Indeed, based on the expression levels of these 3 miRNAs were sufficient to distinguish PSS patients with lymphoma from those without. Two out of these 3 miRNAs were also differentially expressed between the same two groups in the validation cohort.

Conclusion: We have identified 2 miRNAs that are differentially expressed in peripheral blood between PSS patients with lymphoma and those without lymphoma. Identifying the mRNA targets of these miRNAs in PSS may improve our understanding of the pathogenesis of PSS-related lymphoma. Furthermore, miRNAs may be useful biomarkers for PSS-related lymphoma.

Monday 12 August 2013

National Arthritis Week: Meet the expert.

In preparation for National Arthritis Week a lunch and lecture has been arranged for Monday 7th October at Dobbie's Garden World.

Professor Fai Ng will be present to talk about his research into Sjögren’s syndrome and its relationship to other more 'well known' rheumatic conditions such as rheumatoid arthritis and lupus.

Tickets for the event are £10 and are available from Dobbies Garden World customer service desk, by phone 07905827858 or email

The programme also includes lunch and a donation to Arthritis Research UK, a raffle and a Q&A session. For full details, please see below.

Lunch & Lecture
Monday 7 October 2013 at 11.30am
Recognise and Re-energiseidentify the pathways for a better life for primary Sjögren’s syndrome sufferers with Professor Fai Ng.

Dobbies Garden World,
Street House Farm,
NE20 9BT