Monocyte NOTCH2 expression predicts IFN-ß immunogenicity in multiple sclerosis patients.

Multiple sclerosis (MS) is an autoimmune disease characterized by CNS inflammation leading to demyelination and axonal damage. IFN-ß is an established treatment for MS; however, up to 30% of IFN-ß-treated MS patients develop neutralizing antidrug antibodies (nADA), leading to reduced drug bioactivity and efficacy. Mechanisms driving antidrug immunogenicity remain uncertain, and reliable biomarkers to predict immunogenicity development are lacking. Using high-throughput flow cytometry, NOTCH2 expression on CD14+ monocytes and increased frequency of proinflammatory monocyte subsets were identified as baseline predictors of nADA development in MS patients treated with IFN-ß. The association of this monocyte profile with nADA development was validated in 2 independent cross-sectional MS patient cohorts and a prospective cohort followed before and after IFN-ß administration. Reduced monocyte NOTCH2 expression in nADA+ MS patients was associated with NOTCH2 activation measured by increased expression of Notch-responsive genes, polarization of monocytes toward a nonclassical phenotype, and increased proinflammatory IL-6 production. NOTCH2 activation was T cell dependent and was only triggered in the presence of serum from nADA+ patients. Thus, nADA development was driven by a proinflammatory environment that triggered activation of the NOTCH2 signaling pathway prior to first IFN-ß administration.

Hereditary Multiple Exostoses: Clinical, Molecular and Radiologic Survey in 9 Families.

Hereditary multiple exostoses (HME) represents a heterogeneous group of diseases often associated with progressive skeletal deformities. Most frequently, mutations in EXT1 and EXT2 genes with autosomal dominant inheritance are responsible for HME. In our group of 9 families with HME we evaluated the clinical course of the disease and analysed molecular background using Sanger sequencing and MLPA in EXT1 and EXT2 genes. The mean age in our group of patients, when the first exostosis was recognised was 4.5 years (range 2-10 years) and the number of exostoses per one patient documented on X-ray ranged from 2 to 54. Most of the exostoses developed before the growth was completed and they were dominantly localised in the distal femurs, proximal tibia, proximal humerus and distal radius. In all patients, at least one to 8 surgeries were necessary due to complaints and local complications, but neither patient developed malignant transformation. In half of the patients, the disease resulted in short stature. DNA analyses were positive in 7 families. In five probands, different EXT1 gene mutations resulting in premature stop-codon (p.Gly124Argfs*65, p.Leu191*, p.Trp364Lysfs*11, p.Val371Glyfs*10, p.Leu490Profs*31) were found. In two probands, nonsense mutations were found in EXT2 gene (p.Val187Profs*115, p.Cys319fs*46). Five mutations have been novel and two mutations have occurred de novo in probands. Although the risk for malignant transformation is usually low, especially in patients with low number of exostoses, early diagnostics and longitudinal follow up of patients is of a big importance, because early surgery can prevent progression of secondary bone deformities.

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy.

BACKGROUND: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). METHODOLOGY/PRINCIPAL FINDINGS: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. CONCLUSIONS: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin.

Urinary collagen fragments are significantly altered in diabetes: a link to pathophysiology.

BACKGROUND: The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). METHODOLOGY/PRINCIPAL FINDINGS: Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92-95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81-94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81-88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. CONCLUSIONS/SIGNIFICANCE: These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling.