Applying Risk-Based Follow-Up Strategies on the Dutch Breast Cancer Population: Consequences for Care and Costs.

OBJECTIVES: An important aim of follow-up after primary breast cancer treatment is early detection of locoregional recurrences (LRR). This study compares 2 personalized follow-up scheme simulations based on LRR risk predictions provided by a time-dependent prognostic model for breast cancer LRR and quantifies their possible follow-up efficiency. METHODS: Surgically treated early patients with breast cancer between 2003 and 2008 were selected from the Netherlands Cancer Registry. The INFLUENCE nomogram was used to estimate the 5-year annual LRR. Applying 2 thresholds, they were defined according to Youden's J-statistic and a predefined follow-up sensitivity of 95%, respectively. These patient's risk estimations served as the basis for scheduling follow-up visits; 2 personalized follow-up schemes were simulated. The number of potentially saved follow-up visits and corresponding cost savings for each follow-up scheme were compared with the current Dutch breast cancer guideline recommendation and the observed utilization of follow-up on a training and testing cohort. RESULTS: Using LRR risk-predictions for 30 379 Dutch patients with breast cancer from 2003 to 2006 (training cohort), 2 thresholds were calculated. The threshold according to Youden's approach yielded a follow-up sensitivity of 62.5% and a potential saving of 62.1% of follow-up visits and €24.8 million in 5 years. When the threshold corresponding to 95% follow-up sensitivity was used, 17% of follow-up visits and €7 million were saved compared with the guidelines. Similar results were obtained by applying these thresholds to the testing cohort of 11 462 patients from 2007 to 2008. Compared with the observed utilization of follow-up, the potential cost-savings decline moderately. CONCLUSIONS: Personalized follow-up schemes based on the INFLUENCE nomogram's individual risk estimations for breast cancer LRR could decrease the number of follow-up visits if one accepts a limited risk of delayed LRR detection.

Molecular signature characterisation of different inflammatory phenotypes of systemic juvenile idiopathic arthritis.

OBJECTIVES: The International League of Associations for Rheumatology classification criteria define systemic juvenile idiopathic arthritis (SJIA) by the presence of fever, rash and chronic arthritis. Recent initiatives to revise current criteria recognise that a lack of arthritis complicates making the diagnosis early, while later a subgroup of patients develops aggressive joint disease. The proposed biphasic model of SJIA also implies a 'window of opportunity' to abrogate the development of chronic arthritis. We aimed to identify novel SJIA biomarkers during different disease phases. METHODS: Children with active SJIA were subgrouped clinically as systemic autoinflammatory disease with fever (SJIA syst ) or polyarticular disease (SJIA poly ). A discovery cohort of n=10 patients per SJIA group, plus n=10 with infection, was subjected to unbiased label-free liquid chromatography mass spectrometry (LC-MS/MS) and immunoassay screens. In a separate verification cohort (SJIA syst , n=45; SJIA poly , n=29; infection, n=32), candidate biomarkers were measured by multiple reaction monitoring MS (MRM-MS) and targeted immunoassays. RESULTS: Signatures differentiating the two phenotypes of SJIA could be identified. LC-MS/MS in the discovery cohort differentiated SJIA syst from SJIA poly well, but less effectively from infection. Targeted MRM verified the discovery data and, combined with targeted immunoassays, correctly identified 91% (SJIA syst vs SJIA poly ) and 77% (SJIA syst vs infection) of all cases. CONCLUSIONS: Molecular signatures differentiating two phenotypes of SJIA were identified suggesting shifts in underlying immunological processes in this biphasic disease. Biomarker signatures separating SJIA in its initial autoinflammatory phase from the main differential diagnosis (ie, infection) could aid early-stage diagnostic decisions, while markers of a phenotype switch could inform treat-to-target strategies.

Predictive factors and biomarkers for the 2-year outcome of uveitis in juvenile idiopathic arthritis: data from the Inception Cohort of Newly diagnosed patients with Juvenile Idiopathic Arthritis (ICON-JIA) study.

OBJECTIVE: To define predictors for the 2-year outcome in terms of achieving inactivity, subsequent uveitis reactivation and occurrence of uveitis-related complications of JIA-associated uveitis. METHODS: Demographic and clinical parameters and serum samples of JIA-associated uveitis patients enrolled in ICON at ⩽1 year of JIA diagnosis were collected at study enrolment, every 3 months during the first year and subsequently every 6 months. Predictors for the 2-year outcome were evaluated by linear mixed models. RESULTS: Of 954 JIA patients included, uveitis occurred in 106 up to the first 2-year follow-up, with 98 of them having complete ophthalmological documentation. In 81.8% and 80.0% of patients, uveitis inactivity was achieved at the 1- and 2-year follow-up after uveitis onset, respectively. JIA onset after the age of 5 years, no use of topical corticosteroids, and adalimumab treatment were significantly associated with an inactive uveitis for at least 6 months (n = 57). Correlates for subsequent uveitis reactivation (n = 16, 30.2%) were age at uveitis onset ⩽5 years and active disease (clinical Juvenile Arthritis Disease Activity Score >4.5). Uveitis-related complications were present in 29.8% of patients at first uveitis documentation and in 30.7% and 32.8% at 1- and 2-year follow-up, respectively. Older age at JIA onset, short duration between JIA and uveitis onset, high anterior chamber (AC) cell grades, poor visual acuity, and topical steroid use at first uveitis documentation correlated with uveitis-related complications. CONCLUSION: In addition to demographic risk factors, JIA disease and uveitis activity scores and adalimumab are significant predictors for the 2-year outcome of JIA-associated uveitis patients.

Rapid interactome profiling by massive sequencing.

We have developed a high-throughput protein expression and interaction analysis platform that combines cDNA phage display library selection and massive gene sequencing using the 454 platform. A phage display library of open reading frame (ORF) fragments was created from mRNA derived from different tissues. This was used to study the interaction network of the enzyme transglutaminase 2 (TG2), a multifunctional enzyme involved in the regulation of cell growth, differentiation and apoptosis, associated with many different pathologies. After two rounds of panning with TG2 we assayed the frequency of ORFs within the selected phage population using 454 sequencing. Ranking and analysis of more than 120,000 sequences allowed us to identify several potential interactors, which were subsequently confirmed in functional assays. Within the identified clones, three had been previously described as interacting proteins (fibronectin, SMOC1 and GSTO2), while all the others were new. When compared with standard systems, such as microtiter enzyme-linked immunosorbant assay, the method described here is dramatically faster and yields far more information about the interaction under study, allowing better characterization of complex systems. For example, in the case of fibronectin, it was possible to identify the specific domains involved in the interaction.

Serum biomarkers confirming stable remission in inflammatory bowel disease.

Crohn's disease (CD) and ulcerative colitis (UC) have a chronic-remittent course. Optimal management of inflammatory bowel diseases (IBD) relies on early intervention, treat-to-target strategies and a tight disease control. However, it is challenging to assess the risk of relapses in individual patients. We investigated blood-based biomarkers for the confirmation of disease remission in patients with IBD. We retrospectively analyzed samples of 40 IBD patients (30 UC, 10 CD) enrolled in a tight-control follow-up study. Half of the patients had a flare during follow up. Serum was analyzed for S100A12 as well as S100A8/A9 and for 50 further biomarkers in a bead-based multiplex assay. The concentrations of 9 cytokines/chemokines and S100A8/A9 significantly differed in IBD patients with unstable remission (before flares) when compared to IBD patients with stable remission. Although the number of patients was small, ROC curve analyses revealed a number of biomarkers (IL-1ß, IL-1RA, IL-8, IL13, IL-15, IL-21, IL-25, IFN-ß, CXCL9, CXCL10, CXCL11, Galectin-1, G-CSF and S100A8/A9) that were elevated in patients with later occurring relapses. While earlier studies on peripheral biomarkers in IBD are limited to only few analytes, our study using a broad screening approach identified serum biomarkers with the potential to indicate unstable disease control in IBD, which may help to steer individual therapies to maintain remission.

Inhibition of transglutaminase 2 enzymatic activity ameliorates the anti-angiogenic effects of coeliac disease autoantibodies.

OBJECTIVE: Earlier work has demonstrated that serum autoantibodies from coeliac patients targeted against transglutaminase 2 (TG2) inhibit in vitro angiogenesis. The aim of this study was to establish whether coeliac patient-derived monoclonal TG2-targeted antibodies produced by recombination technology exert similar anti-angiogenic effects to serum-derived coeliac autoantibodies. In addition, we studied whether the monoclonal patient autoantibodies modulate endothelial cell TG2 activity and whether such modulation is related to the anti-angiogenic effects. MATERIAL AND METHODS: The influence of coeliac patient-derived monoclonal TG2-targeted antibodies on endothelial cell tubule formation was studied using a three-dimensional angiogenic cell culture model. Endothelial cell TG2 enzymatic activity was determined by means of a live-cell enzyme-linked immunosorbent assay. RESULTS: Coeliac patient-derived monoclonal TG2-targeted antibodies produced by recombination technology inhibited endothelial tubule formation and enhanced the crosslinking activity of TG2. When this enzymatic activity was inhibited using site-directed irreversible TG2 inhibitors in the presence of autoantibodies, in vitro angiogenesis reverted to the control level. CONCLUSIONS: Since we found a significant negative correlation between endothelial cell angiogenesis and TG2 activity, we suggest that the anti-angiogenic effects of coeliac patient-derived TG2-targeted autoantibodies are exerted by enhanced enzymatic activity of TG2.

Predicting the risk of locoregional recurrence after early breast cancer: an external validation of the Dutch INFLUENCE-nomogram with clinical cancer registry data from Germany.

PURPOSE: Follow-up after breast cancer treatment aims for an early detection of locoregional breast cancer recurrences (LRR) to improve the patients' outcome. By estimating individual's 5-year recurrence-risks, the Dutch INFLUENCE-nomogram can assist health professionals and patients in developing personalized risk-based follow-up pathways. The objective of this study is to validate the prediction tool on non-Dutch patients. MATERIAL AND METHODS: Data for this external validation derive from a large clinical cancer registry in southern Germany, covering a population of 1.1 million. Patients with curative resection of early-stage breast cancer, diagnosed between 2000 and 2012, were included in the analysis (n = 6520). For each of them, an individual LRR-risk was estimated by the INFLUENCE-nomogram. Its predictive ability was tested by comparing estimated and observed LRR-probabilities using the Hosmer-Lemeshow goodness-of-fit test and C-statistics. RESULTS: In the German validation-cohort, 2.8% of the patients developed an LRR within 5 years after primary surgery (n = 184). While the INFLUENCE-nomogram generally underestimates the actual LRR-risk of the German patients (p < 0.001), its discriminative ability is comparable to the one observed in the original Dutch modeling-cohort (C-statistic German validation-cohort: 0.73, CI 0.69-0.77 vs. C-statistic Dutch modeling-cohort: 0.71, CI 0.69-0.73). Similar results were obtained in most of the subgroup analyses stratified by age, type of surgery and intrinsic biological subtypes. CONCLUSION: The outcomes of this external validation underline the generalizability of the INFLUENCE-nomogram beyond the Dutch population. The model performance could be enhanced in future by incorporating additional risk factors for LRR.

A survey of avian Mycoplasma species for neuraminidase enzymatic activity.

Among 23 currently recognized avian Mycoplasma (AM) species only Mycoplasma gallisepticum, Mycoplasma synoviae, Mycoplasma meleagridis and Mycoplasma iowae cause disease and loss of production in chickens and/or turkeys. Because neuraminidases are considered virulence factors in many pathogenic microorganisms the aim of our study was to determine which AM species possess neuraminidase enzymatic activity (NEAC). Small samples of AM cells were assayed for NEAC using the chromogenic substrate 5-bromo-4-chloro-3-indolyl-alpha-d-N-acetylneuraminic acid. In the case of positive NEAC reaction the substrate gave the insoluble indigoblue product what enabled simple test and easy estimation of NEAC. M. gallisepticum and M. synoviae which share sequences of the gene encoding neuraminidase (sialidase NanH) exhibited considerable levels of NEAC. However, NEAC levels differed among their strains, as well as among cultures of different strains. Only certain cultures of the type strain of M. meleagridis showed NEAC, whereas among six serovars of M. iowae only serovar I (type strain 695) showed NEAC. Weak NEAC was detectable in M. anseris, M. cloacale and M. pullorum, whereas the type strain of M. corogypsi (BV1) showed strong NEAC. Our study provides novel informations about NEAC in AM species and suggests that higher invasiveness and possibly, the pathological processes might be associated with their NEAC.

Gene expression modulation in chicken macrophages exposed to Mycoplasma synoviae or Escherichia coli.

Mycoplasma synoviae and Escherichia coli are two avian pathogens that exhibit markedly different mechanisms for infection and pathogenicity and may be expected to manipulate the host innate immune response differently. The aim of this study was to determine the extent of modulated genes and make a comparison between the transcriptomes of chicken macrophages exposed to either M. synoviae type strain WVU 1853 (MS) or avian pathogenic E. coli strain V-G (APEC). To analyze temporal gene expression profile of monocyte-derived macrophages (MDM) and HD11 cell line macrophages after each exposure, two avian immunity microarrays were used: the avian macrophage microarray (AMM) and the avian innate immunity microarray (AIIM). The quantity of MS-modulated genes was estimated in three experiments, using both microarrays. A cross-section revealed 14 AMM/AIIM genetic elements that were modulated in both types of macrophages. Additionally, to compare immunomodulatory activity of MS and APEC, MDM were exposed to each pathogen and gene modulation was detected by AIIM microarray. This study revealed 157 elements uniquely modulated by MS and 1603 elements uniquely modulated by APEC. AIIM microarray analysis also revealed a core set of 146 elements modulated by both pathogens, with generally higher induction/repression levels after APEC exposure. Validation of selected gene expression was done by quantitative real time RT-PCR. The study shows higher transcription levels of IL-1beta, IL-6, iNOS, NCF1, peroxiredoxin 1 and cathepsin L genes after MDM exposure to APEC than after exposure to MS. Surprisingly, complement component C3 gene was repressed after MDM exposure to APEC, while being induced after exposure to MS.

Identification of major immunogenic proteins of Mycoplasma synoviae isolates.

Mycoplasma synoviae isolates differ in patterns of immunogenic proteins, but most of them have not been identified yet. The main aim of this study was their identification in two closely related M. synoviae isolates, ULB 02/P4 and ULB 02/OV6, recovered recently from chickens in Slovenia. N-terminal sequencing identified 17 M. synoviae proteins. Amongst them were 14 major, highly expressed but previously unidentified proteins, including enzymes, chaperones and putative lipoproteins. ULB 02/P4 proteins with increasing molecular weight (M(w)) in the region above the lipoprotein MSPB (approximately 40 kDa) were elongation factor EF-Tu, enolase, NADH oxidase, haemagglutinin MSPA, ATP synthase beta chain, trigger factor, pyruvate kinase and chaperone DnaK. Enolase (approximately 47 kDa) seemed to be immunogenic for chickens infected with M. synoviae, whereas EF-Tu, which might cross-react with antibodies to the P1 adhesin of Mycoplasma pneumoniae, was not. ULB 02/OV6 synthesized several immunogenic proteins and those with M(w) of approximately 70, 78, 82, 90, 110 and 160 kDa, cross-reacted with antibodies to Mycoplasma gallisepticum. They remain to be identified, because besides putative lipoproteins, protein bands of 78, 82, 85 and 110 kDa contained also dehydrogenase PdhD, elongation factor EF-G, enzyme PtsG and putative neuraminidase, respectively.

Risk Factors and Biomarkers for the Occurrence of Uveitis in Juvenile Idiopathic Arthritis: Data From the Inception Cohort of Newly Diagnosed Patients With Juvenile Idiopathic Arthritis Study.

OBJECTIVE: To analyze the prognostic value of demographic, clinical, and therapeutic factors and laboratory biomarkers and to assess their role in predicting uveitis occurrence in patients with juvenile idiopathic arthritis (JIA). METHODS: Patients with JIA were enrolled within the first year after JIA diagnosis. Demographic and clinical parameters were documented. Serum samples were collected at study enrollment, at 3-month follow-up visits within the first year, and then every 6 months. A multivariable Cox regression analysis was performed to evaluate the impact of demographic, clinical, laboratory, and therapeutic parameters on uveitis onset. RESULTS: We included 954 JIA patients (67.2% female, 54.2% antinuclear antibody [ANA] positive, mean ± SD age at onset 7.1 ± 4.6 years). Uveitis occurred in 133 patients (observation period 44.5 months). Young age at JIA onset and ANA positivity were significantly associated with the onset of uveitis (both P < 0.001). Treatment of arthritis with methotrexate alone (hazard ratio [HR] 0.18 [95% confidence interval (95% CI) 0.12-0.29], P < 0.001) or combined with etanercept (HR 0.10 [95% CI 0.04-0.23], P < 0.001) or adalimumab (HR 0.09 [95% CI 0.01-0.61], P = 0.014) reduced the risk of uveitis onset and the occurrence of uveitis-related complications. Predictors of uveitis onset included elevated erythrocyte sedimentation rate at baseline (HR 2.36 [95% CI 1.38-4.02], P = 0.002) and continuing moderate or high disease activity during follow-up as measured by the 10-joint clinical Juvenile Arthritis Disease Activity Score (HR 4.30 [95% CI 2.51-7.37], P < 0.001). Additionally, S100A12 levels ≥250 ng/ml at baseline were significantly associated with the risk of uveitis (HR 2.10 [95% CI 1.15-3.85], P = 0.016). CONCLUSION: Apart from demographic risk factors and treatment modalities, JIA disease activity scores and laboratory biomarkers could be used to better define the group of JIA patients at high risk of uveitis onset.

Chicken toll-like receptor 3 recognizes its cognate ligand when ectopically expressed in human cells.

Recognition of pathogens by toll-like receptors (TLRs) causes activation of signaling cascades that trigger cytokine secretion and, ultimately, innate immunity. Genes encoding proteins with substantial homology to mammalian TLR1, TLR2, TLR3, TLR4, TLR5, and TLR7 are present in the chicken genome, whereas orthologs of TLR8, TLR9, and TLR10 seem to be defective or missing. Except for chicken TLR2 (ChTLR2), which was previously shown to recognize lipopeptides and lipopolysaccharides (LPS), the ligand specificity of ChTLRs had not been determined. We found that polyI:C, LPS, R848, S-28463, and ODN2006, which are specifically recognized by TLR3, TLR4, TLR7/8, and TLR9 in mammals, induced substantial amounts of type I interferon (IFN) and interleukin-6 (IL-6) in freshly prepared chicken splenocytes. To determine the ligand specificity of ChTLR3 and ChTLR7, we used a standard reporter assay frequently employed for analysis of mammalian TLRs. Neither S-28463 nor any other TLR ligand induced reporter activity in human 293 cells expressing ChTLR7. However, human 293 cells expressing ChTLR3 strongly and specifically responded to polyI:C, demonstrating that this chicken receptor represents a true ortholog of mammalian TLR3.

Mycoplasma synoviae lipoprotein MSPB, the N-terminal part of VlhA haemagglutinin, induces secretion of nitric oxide, IL-6 and IL-1beta in chicken macrophages.

Mycoplasma synoviae is a major pathogen of chickens and turkeys, causing respiratory disease and infectious synovitis. M. synoviae haemagglutinin VlhA is an abundant surface-exposed lipoprotein and immunodominant antigen. Post-translational cleavage of VlhA generates two proteins, MSPB and MSPA. MSPB, the amino-terminal end of VlhA, is a lipoprotein of about 40-50 kDa but can appear in truncated forms (tMSPB) of about 20-30 kDa. The aim of this study was to determine whether MSPB and tMSPB can stimulate chicken macrophages to secrete NO and cytokines. Macrophages derived from chicken monocytes (MDM) or the MQ-NCSU macrophage cell line were stimulated with M. synoviae protein extracts containing MSPB or tMSPB, as well as with purified MSPB and tMSPB. Proteins from detergent extractions induced IL-6 secretion in MDM and NO secretion in MQ-NCSU. Both MSPB and tMSPB were capable of inducing NO secretion in MQ-NCSU, as well as IL-6 and IL-1beta in MDM. The activity of IL-6 induced by purified tMSPB was similar to the effect of 60 pg/ml of recombinant chicken IL-6. The effect of IL-1beta induced by tMSPB was comparable to the effect of 10 ng/ml of recombinant IL-1beta. Whereas all samples containing MSPB were able to induce NO, IL-6 and IL-1beta, it seemed that the purified tMSPB of about 20 kDa was the most potent in its ability to induce IL-6 and IL-1beta in MDM. Compared to MSPB, tMSPB lacks about 200 amino acids in its carboxyl-terminal part. Therefore, our results suggest that the major part of the stimulating activity is associated with the amino-terminal part of MSPB, most likely with its lipid moiety.

Alarmins firing arthritis: Helpful diagnostic tools and promising therapeutic targets.

Alarmins are endogenous molecules with homeostatic roles that have reached the focus of research in inflammatory arthritis in the last two decades, mostly due to their ability to indicate tissue related damage after active or passive release from injured cells. From HMGB1, S100A8/A9 and S100A12 proteins, over heat-shock proteins (HSPs) and purine metabolites (e.g. uric acid, ATP) to altered matrix proteins and interleukin-33 (IL-33), a number of alarmins have been determined until now as having a role in rheumatoid arthritis, psoriatic and juvenile idiopathic arthritis, as well as spondyloarthritis and gout. Although formerly being linked to initiation and chronification of inflammatory arthritis, driving auto- and paracrine inflammatory loops, more recent research has also unraveled the alarmins' role in the crosstalk between innate and adaptive immunity and in resolution of inflammation. Providing a state-of-the-art overview of known alarmins, this review lists the known modes of action and pathologic contribution of alarmins to inflammatory arthritis, as well as biomarker potential of alarmins in the clinical setting for tracking disease severity. Based upon research on animal experimental models (CIA, AIA) and clinical trials, a look is made into potentially viable strategies for modifying alarmin secretion and their target receptor (e.g. TLR, RAGE) interaction with the purpose of attenuating arthritic disease.

Review of biomarkers in systemic juvenile idiopathic arthritis: helpful tools or just playing tricks?

BACKGROUND: Diagnosing systemic juvenile idiopathic arthritis (SJIA) can be extremely challenging if typical arthritis is lacking. A variety of biomarkers have been described for the diagnosis and management of SJIA. However, very few markers have been well-validated. In addition, increasing numbers of biomarkers are identified by high throughput or multi-marker panels. METHOD: We identified diagnostic or prognostic biomarkers by systematic literature review, evaluating each according to a predefined level of verification, validation or clinical utility. Diagnostic biomarkers were those identifying SJIA versus (1) non-SJIA conditions or healthy controls (HC) or (2) other non-systemic JIA subtypes. Prognostic biomarkers were those specifically tested for the prediction of (1) disease flare, (2) increased disease activity +/- discrimination of active versus inactive disease, or (3) macrophage activation syndrome (MAS). RESULTS: Fifty-five studies fulfilled the inclusion criteria identifying 68 unique biomarkers, of which 50/68 (74 %) were investigated by only a single research group. Candidate marker verification and clinical utility was evaluated according to whether markers were readily and reliably measurable, investigated by independent study groups, discovered by more than one method (i.e. verified markers) and validated in independent cohorts. This evaluation revealed diagnostic biomarkers of high interest for further evaluation in the diagnostic approach to SJIA that included heme oxygenase-1, interleukin-6 (IL-6), IL-12, IL-18, osteoprotegerin, S100 calcium-binding protein A12 (S100A12) and S100A8/A9. CONCLUSION: In summary, a number of biomarkers were identified, though most had limited evidence for their use. However, our findings combined with the identified studies could inform validation studies, whether in single or multi-marker assays, which are urgently needed.

Mycoplasma gallisepticum hemagglutinin V1hA, pyruvate dehydrogenase PdhA, lactate dehydrogenase, and elongation factor Tu share epitopes with Mycoplasma imitans homologues.

Mycoplasma gallisepticum is a major pathogen of poultry. Mycoplasma imitans is genetically and antigenically closely related to M. gallisepticum, but so far, only a few proteins of M. imitans have been identified as sharing epitopes with M. gallisepticum. In this study, we identified three proteins of M. gallisepticum that share with M. imitans epitopes defined by monoclonal antibodies (MAbs). MAb 9D4 reacted with the 67-kD hemagglutinin V1hA (previously termed pMGA) of M. gallisepticum and with its continuously expressed 40-kD protein. This MAb also reacted with a 40-kD protein of M. imitans, but not with its putative V1hA. Two-dimensional (2D) immunoblots of M. gallisepticum strains showed that their 40-kD proteins reacting with MAb 9D4 are expressed as major forms with isoelectric points (pI) around 6, and also as less-abundant forms differing in pI. In M. imitans, major forms of 40-kD proteins recognized by MAb 9D4 had pI around 6, whereas minor forms had pI between 5.5 and 5.8. The N-terminal sequence of the M. gallisepticum 40-kD protein recognized by MAb 9D4 strongly indicates that this protein is pyruvate dehydrogenase E1, subunit alpha (PdhA protein, also termed AcoA). The position of elongation factor Tu (EF-Tu), detected by the reference MAb GB8, was very similar in the 2D proteome maps of M. gallisepticum and M. imitans (MW of about 45 kD; pI - 5.6). In both M. gallisepticum and M. imitans, MAb 7G1 reacted with proteins of about 36 kD with similar charges (major forms with pI of about 8). The position of this protein in the proteome map of M. gallisepticum and its N-terminal sequence strongly suggest that MAb 7G1 recognizes lactate (malate) dehydrogenase (Ldh or Mdh). Comparison of 2D proteomes of 10 M. gallisepticum strains indicated that positions of EF-Tu, PdhA, and Ldh proteins are rather consistent and can be used as reference points in further analyses of the M. gallisepticum proteome.

RhoB is associated with the anti-angiogenic effects of celiac patient transglutaminase 2-targeted autoantibodies.

Celiac patient-derived anti-transglutaminase 2 (TG2) antibodies disturb several steps in angiogenesis, but the detailed molecular basis is not known. Therefore, we here analyzed by microarray technology the expression of a set of genes related to angiogenesis and endothelial cell biology in order to identify factors that could explain our previous data related to vascular biology in the context of celiac disease. To this end, in vitro models using human umbilical vein endothelial cells (HUVECs) or in vivo models of angiogenesis were used. A total of 116 genes were analyzed after treatment with celiac patient autoantibodies against TG2. Compared to treatment with control IgA celiac patient, total IgA induced a consistent expression change of 10 genes, the up-regulation of four and down-regulation of six. Of these genes the up-regulated RhoB was selected for further studies. RhoB expression was found to be up-regulated at both messenger RNA and protein level in response to celiac patient total IgA as well as anti-TG2-specific antibody derived from a celiac patient. Interestingly, down-regulation of RhoB by specific small interfering RNA treatment in endothelial cells could rescue the deranged endothelial length and tubule formation caused by celiac disease autoantibodies. RhoB function is controlled by its post-translational modification by farnesylation. This modification of RhoB required for its correct function can be prevented by the cholesterol lowering drug simvastatin, which was also able to abolish the anti-angiogenic effects of celiac anti-TG2 autoantibodies. Taken together, our results would suggest that RhoB plays a key role in the response of endothelial cells to celiac disease-specific anti-TG2 autoantibodies.

Analysis of a simulated microarray dataset: comparison of methods for data normalisation and detection of differential expression (open access publication).

Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.

The EADGENE Microarray Data Analysis Workshop (open access publication).

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.

Analysis of the real EADGENE data set: comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (open access publication).

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.