Analysis of genetic variation contributing to measured speed in Thoroughbreds identifies genomic regions involved in the transcriptional response to exercise

Despite strong selection for athletic traits in Thoroughbred horses, there is marked variation in speed and aptitude for racing performance within the breed. Using global positioning system monitoring during exercise training, we measured speed variables and temporal changes in speed with age to derive phenotypes for GWAS. The aim of the study was to test the hypothesis that genetic variation contributes to variation in end‐point physiological traits, in this case galloping speed measured during field exercise tests. Standardisation of field‐measured phenotypes was attempted by assessing horses exercised on the same gallop track and managed under similar conditions by a single trainer. PCA of six key speed indices captured 73.9% of the variation with principal component 1 (PC1). Verifying the utility of the phenotype, we observed that PC1 (median) in 2‐year‐old horses was significantly different among elite, non‐elite and unraced horses (P T SNP genotypes. A GWAS for PC1 in 2‐year‐old horses (n = 122) identified four SNPs reaching the suggestive threshold for association (P < 4.80 × 10−5), defining a 1.09 Mb candidate region on ECA8 containing the myosin XVIIIB (MYO18B) gene. In a GWAS for temporal change in PC1 with age (n = 168), five SNPs reached the suggestive threshold for association and defined candidate regions on ECA2 and ECA11. Both regions contained genes that are significantly differentially expressed in equine skeletal muscle in response to acute exercise and training stimuli, including MYO18A. As MYO18A plays a regulatory role in the skeletal muscle response to exercise, the identified genomic variation proximal to the myosin family genes may be important for the regulation of the response to exercise and training

Prediction of retinopathy of prematurity using the screening algorithm WINROP in a Mexican population of preterm infants

Objective: To retrospectively validate the WINROP (weight, insulin-like growth factor I, neonatal, retinopathy of prematurity [ROP]) algorithm in identification of type 1 ROP in a Mexican population of preterm infants. Methods: In infants admitted to the neonatal intensive care unit at Hospital Civil de Guadalajara from 2005 to 2010, weight measurements had been recorded once weekly for 192 very preterm infants (gestational age [GA] <32 weeks) and for 160 moderately preterm infants (GA ?32 weeks). Repeated eye examinations had been performed and maximal ROP stage had been recorded. Data are part of a casecontrol database for severe ROP risk factors. Results: Type 1 ROP was found in 51.0% of very preterm and 35.6% of moderately preterm infants. The WINROP algorithm correctly identified type 1 ROP in 84.7% of very preterm infants but in only 5.3% of moderately preterm infants. For infants with GA less than 32 weeks, the specificity was 26.6%, and for those with GA 32 weeks or more, it was 88.3%. Conclusions: In this Mexican population of preterm infants, WINROP detected type 1 ROP early in 84.7% of very preterm infants and correctly identified 26.6% of infants who did not develop type 1 ROP. Uncertainties in dating of pregnancies and differences in postnatal conditions may be factors explaining the different outcomes of WINROP in this population