Chronic joint disease caused by persistent Chikungunya virus infection is controlled by the adaptive immune response

Chikungunya virus (CHIKV) is a reemerging mosquito-borne pathogen that causes incapacitating disease in humans characterized by intense joint pain that can persist for weeks, months, or even years. Although there is some evidence of persistent CHIKV infection in humans suffering from chronic rheumatologic disease symptoms, little is known about chronic disease pathogenesis, and no specific therapies exist for acute or chronic CHIKV disease. To investigate mechanisms of chronic CHIKV-induced disease, we utilized a mouse model and defined the duration of CHIKV infection in tissues and the associated histopathological changes. Although CHIKV RNA was readily detectable in a variety of tissues very early after infection, CHIKV RNA persisted specifically in joint-associated tissues for at least 16 weeks. Inoculation of Rag1(−/−) mice, which lack T and B cells, resulted in higher viral levels in a variety of tissues, suggesting that adaptive immunity controls the tissue specificity and persistence of CHIKV infection. The presence of CHIKV RNA in tissues of wild-type and Rag1(−/−) mice was associated with histopathological evidence of synovitis, arthritis, and tendonitis; thus, CHIKV-induced persistent arthritis is not mediated primarily by adaptive immune responses. Finally, we show that prophylactic administration of CHIKV-specific monoclonal antibodies prevented the establishment of CHIKV persistence, whereas therapeutic administration had tissue-specific efficacy. These findings suggest that chronic musculoskeletal tissue pathology is caused by persistent CHIKV infection and controlled by adaptive immune responses. Our results have significant implications for the development of strategies to mitigate the disease burden associated with CHIKV infection in humans

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST

Genomics in neurodevelopmental disorders: an avenue to personalized medicine

Despite the remarkable number of scientific breakthroughs of the last 100 years, the treatment of neurodevelopmental disorders (e.g., autism spectrum disorder, intellectual disability) remains a great challenge. Recent advancements in genomics, such as whole-exome or whole-genome sequencing, have enabled scientists to identify numerous mutations underlying neurodevelopmental disorders. Given the few hundred risk genes that have been discovered, the etiological variability and the heterogeneous clinical presentation, the need for genotype — along with phenotype- based diagnosis of individual patients has become a requisite. In this review we look at recent advancements in genomic analysis and their translation into clinical practice