A Novel Unstable Duplication Upstream of HAS2 Predisposes to a Breed-Defining Skin Phenotype and a Periodic Fever Syndrome in Chinese Shar-Pei Dogs

Hereditary periodic fever syndromes are characterized by recurrent episodes of fever and inflammation with no known pathogenic or autoimmune cause. In humans, several genes have been implicated in this group of diseases, but the majority of cases remain unexplained. A similar periodic fever syndrome is relatively frequent in the Chinese Shar-Pei breed of dogs. In the western world, Shar-Pei have been strongly selected for a distinctive thick and heavily folded skin. In this study, a mutation affecting both these traits was identified. Using genome-wide SNP analysis of Shar-Pei and other breeds, the strongest signal of a breed-specific selective sweep was located on chromosome 13. The same region also harbored the strongest genome-wide association (GWA) signal for susceptibility to the periodic fever syndrome (praw = 2.3×10−6, pgenome = 0.01). Dense targeted resequencing revealed two partially overlapping duplications, 14.3 Kb and 16.1 Kb in size, unique to Shar-Pei and upstream of the Hyaluronic Acid Synthase 2 (HAS2) gene. HAS2 encodes the rate-limiting enzyme synthesizing hyaluronan (HA), a major component of the skin. HA is up-regulated and accumulates in the thickened skin of Shar-Pei. A high copy number of the 16.1 Kb duplication was associated with an increased expression of HAS2 as well as the periodic fever syndrome (p<0.0001). When fragmented, HA can act as a trigger of the innate immune system and stimulate sterile fever and inflammation. The strong selection for the skin phenotype therefore appears to enrich for a pleiotropic mutation predisposing these dogs to a periodic fever syndrome. The identification of HA as a major risk factor for this canine disease raises the potential of this glycosaminoglycan as a risk factor for human periodic fevers and as an important driver of chronic inflammation

Genetic Control of Canine Leishmaniasis: Genome-Wide Association Study and Genomic Selection Analysis

Background: the current disease model for leishmaniasis suggests that only a proportion of infected individuals develop clinical disease, while others are asymptomatically infected due to immune control of infection. The factors that determine whether individuals progress to clinical disease following Leishmania infection are unclear, although previous studies suggest a role for host genetics. Our hypothesis was that canine leishmaniasis is a complex disease with multiple loci responsible for the progression of the disease from Leishmania infection. Methodology/Principal Findings: genome-wide association and genomic selection approaches were applied to a population-based case-control dataset of 219 dogs from a single breed (Boxer) genotyped for ~170,000 SNPs. Firstly, we aimed to identify individual disease loci; secondly, we quantified the genetic component of the observed phenotypic variance; and thirdly, we tested whether genome-wide SNP data could accurately predict the disease. Conclusions/Significance: we estimated that a substantial proportion of the genome is affecting the trait and that its heritability could be as high as 60%. Using the genome-wide association approach, the strongest associations were on chromosomes 1, 4 and 20, although none of these were statistically significant at a genome-wide level and after correcting for genetic stratification and lifestyle. Amongst these associations, chromosome 4: 61.2-76.9 Mb maps to a locus that has previously been associated with host susceptibility to human and murine leishmaniasis, and genomic selection estimated markers in this region to have the greatest effect on the phenotype. We therefore propose these regions as candidates for replication studies. An important finding of this study was the significant predictive value from using the genomic information. We found that the phenotype could be predicted with an accuracy of ~0.29 in new samples and that the affection status was correctly predicted in 60% of dogs, significantly higher than expected by chance, and with satisfactory sensitivity-specificity values (AUC = 0.63)

Parkinson's disease severity at 3 years can be predicted from non-motor symptoms at baseline

Objective: The aim of this study is to present a predictive model of Parkinson's disease (PD) global severity, measured with the Clinical Impression of Severity Index for Parkinson's Disease (CISI-PD). Methods: This is an observational, longitudinal study with annual follow-up assessments over 3 years (four time points). A multilevel analysis and multiple imputation techniques were performed to generate a predictive model that estimates changes in the CISI-PD at 1, 2, and 3 years. Results: The clinical state of patients (CISI-PD) significantly worsened in the 3-year follow-up. However, this change was of small magnitude (effect size: 0.44). The following baseline variables were significant predictors of the global severity change: baseline global severity of disease, levodopa equivalent dose, depression and anxiety symptoms, autonomic dysfunction, and cognitive state. The goodness-of-fit of the model was adequate, and the sensitive analysis showed that the data imputation method applied was suitable. Conclusion: Disease progression depends more on the individual's baseline characteristics than on the 3-year time period. Results may contribute to a better understanding of the evolution of PD including the non-motor manifestations of the disease.The Spanish Longitudinal PD Patient Study (Estudio longitudinal de pacientes con enfermedad de Parkinson) was supported by an Intramural Research Programme grant from the Carlos III Institute of Health (Code: EPY1271/05). Partial funding was also obtained from the following grants: ENVACES (MINECO/FEDER/UE, ref. CSO2015-64115-R) and ENCAGE-CM (Comunidad de Madrid, ref. S2015/HUM-3367