Sarcoglycan A mutation in miniature dachshund dogs causes limb-girdle muscular dystrophy 2D.

BACKGROUND: A cohort of related miniature dachshund dogs with exercise intolerance, stiff gait, dysphagia, myoglobinuria, and markedly elevated serum creatine kinase activities were identified. METHODS: Muscle biopsy histopathology, immunofluorescence microscopy, and western blotting were combined to identify the specific pathologic phenotype of the myopathy, and whole genome SNP array genotype data and whole genome sequencing were combined to determine its genetic basis. RESULTS: Muscle biopsies were dystrophic. Sarcoglycanopathy, a form of limb-girdle muscular dystrophy, was suspected based on immunostaining and western blotting, where α, ß, and γ-sarcoglycan were all absent or reduced. Genetic mapping and whole genome sequencing identified a premature stop codon mutation in the sarcoglycan A subunit gene (SGCA). Affected dachshunds were confirmed on several continents. CONCLUSIONS: This first SGCA mutation found in dogs adds to the literature of genetic bases of canine muscular dystrophies and their usefulness as comparative models of human disease.

Spatial scale effects in environmental risk-factor modelling for diseases.

Studies attempting to identify environmental risk factors for diseases can be seen to extract candidate variables from remotely sensed datasets, using a single buffer-zone surrounding locations from where disease status are recorded. A retrospective case-control study using canine leptospirosis data was conducted to verify the effects of changing buffer-zones (spatial extents) on the risk factors derived. The case-control study included 94 case dogs predominantly selected based on positive polymerase chain reaction (PCR) test for leptospires in urine, and 185 control dogs based on negative PCR. Land cover features from National Land Cover Dataset (NLCD) and Kansas Gap Analysis Program (KS GAP) around geocoded addresses of cases/controls were extracted using multiple buffers at every 500 m up to 5,000 m, and multivariable logistic models were used to estimate the risk of different land cover variables to dogs. The types and statistical significance of risk factors identified changed with an increase in spatial extent in both datasets. Leptospirosis status in dogs was significantly associated with developed high-intensity areas in models that used variables extracted from spatial extents of 500-2000 m, developed medium-intensity areas beyond 2,000 m and up to 3,000 m, and evergreen forests beyond 3,500 m and up to 5,000 m in individual models in the NLCD. Significant associations were seen in urban areas in models that used variables extracted from spatial extents of 500-2,500 m and forest/woodland areas beyond 2,500 m and up to 5,000 m in individual models in Kansas gap analysis programme datasets. The use of ad hoc spatial extents can be misleading or wrong, and the determination of an appropriate spatial extent is critical when extracting environmental variables for studies. Potential work-arounds for this problem are discussed.