Antibodies Against Three Novel Peptides in Early Axial Spondyloarthritis Patients From Two Independent Cohorts.

OBJECTIVE: This study was undertaken to identify novel autoantibodies in axial spondyloarthritis (SpA) and determine their diagnostic potential in patients with early axial SpA and controls from 2 independent cohorts. METHODS: An axial SpA complementary DNA phage display library was used to screen for novel IgG antibodies in plasma from patients with early axial SpA. The presence of these antibodies against novel peptides (i.e., peptides identified in an early axial SpA cohort from Hasselt University, designated UH-axSpA) was determined by enzyme-linked immunosorbent assay in 76 patients with early axial SpA, 75 controls with nonspecific chronic low back pain, 60 patients with rheumatoid arthritis, and 94 healthy controls from the UH cohort. Antibody reactivity to these novel peptides was further validated in 174 patients with axial SpA (of whom 79 had early axial SpA) from the University Hospitals Leuven (Bio)SPAR (Spondyloarthritis [Biologics]) cohort. RESULTS: We identified antibodies to 9 novel UH-axSpA peptides, corresponding to randomly formed peptides and to a novel axial SpA autoantigen, double homeobox protein 4. Antibodies to 3 UH-axSpA peptides with the highest positive likelihood ratio (LR) for a diagnosis of axial SpA were present in significantly more patients with early axial SpA from the UH and (Bio)SPAR cohorts (14.2% [22/155]) compared to controls with chronic low back pain (5% [4/75]), resulting in 95% specificity. The positive LR for confirming axial SpA using antibodies to these 3 UH-axSpA peptides was 2.7, which is higher than the LR obtained with the currently used laboratory marker C-reactive protein. Testing for antibodies to these 3 UH-axSpA peptides in patients with chronic low back pain increased the posttest probability of a diagnosis of axial SpA from 79% to 91%. CONCLUSION: Antibodies to 3 UH-axSpA peptides could provide a novel tool in the diagnosis of a subset of axial SpA patients.

Spatiotemporal Evolution of Ebola Virus Disease at Sub-National Level during the 2014 West Africa Epidemic: Model Scrutiny and Data Meagreness.

BACKGROUND: The Ebola outbreak in West Africa has infected at least 27,443 individuals and killed 11,207, based on data until 24 June, 2015, released by the World Health Organization (WHO). This outbreak has been characterised by extensive geographic spread across the affected countries Guinea, Liberia and Sierra Leone, and by localized hotspots within these countries. The rapid recognition and quantitative assessment of localised areas of higher transmission can inform the optimal deployment of public health resources. METHODS: A variety of mathematical models have been used to estimate the evolution of this epidemic, and some have pointed out the importance of the spatial heterogeneity apparent from incidence maps. However, little is known about the district-level transmission. Given that many response decisions are taken at sub-national level, the current study aimed to investigate the spatial heterogeneity by using a different modelling framework, built on publicly available data at district level. Furthermore, we assessed whether this model could quantify the effect of intervention measures and provide predictions at a local level to guide public health action. We used a two-stage modelling approach: a) a flexible spatiotemporal growth model across all affected districts and b) a deterministic SEIR compartmental model per district whenever deemed appropriate. FINDINGS: Our estimates show substantial differences in the evolution of the outbreak in the various regions of Guinea, Liberia and Sierra Leone, illustrating the importance of monitoring the outbreak at district level. We also provide an estimate of the time-dependent district-specific effective reproduction number, as a quantitative measure to compare transmission between different districts and give input for informed decisions on control measures and resource allocation. Prediction and assessing the impact of control measures proved to be difficult without more accurate data. In conclusion, this study provides us a useful tool at district level for public health, and illustrates the importance of collecting and sharing data.