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OBJECTIVE To identify genetic associations with primary glaucoma (PG) in American Cocker Spaniels using a genome-wide association study (GWAS). ANIMALS A nationwide ambidirectional case–control cohort study was performed in American Cocker Spaniels that had an ophthalmic examination performed by a veterinarian. Ninety-four dogs with PG (cases) and 111 dogs without glaucoma (controls) met phenotypic criteria and had a blood sample collected after receiving informed owner consent. PROCEDURES Genomic DNA was extracted from whole blood samples and genotyped (CanineHD BeadChip, Illumina Inc). A case–control GWAS using a linear mixed model was performed, and 3 significance thresholds were calculated (1) using a Bonferroni correction on all single nucleotide polymorphisms (SNPs) included in the GWAS, (2) using a Bonferroni correction on only the unlinked SNPs from a pruned data set, and (3) using 10,000 random phenotype permutations. RESULTS Following genotype data quality control, 89 cases and 93 controls were included in the GWAS. We identified an association on canine chromosome (CFA10); however, it did not reach statistical significance. Potential candidate genes within the surrounding linkage disequilibrium interval include coiled-coil domain containing 85A (CCDC85A) and extracellular growth factor containing fibulin extracellular matrix protein 1 (EFEMP1). CLINICAL RELEVANCE Primary glaucoma in the American Cocker Spaniel is a complex heterogeneous disease that may be influenced by a locus on CFA10. The candidate genes CCDC85A and EFEMP1 within the identified linkage disequilibrium interval have been shown to be involved in human open-angle glaucoma. [ABSTRACT FROM AUTHOR]

Feline chronic enteropathy is a poorly defined condition of older cats that encompasses chronic enteritis to low-grade intestinal lymphoma. The histological evaluation of lymphocyte numbers and distribution in small intestinal biopsies is crucial for classification and grading. However, conventional histological methods for lymphocyte quantification have low interobserver agreement, resulting in low diagnostic reliability. This study aimed to develop and validate an artificial intelligence (AI) model to detect intraepithelial and lamina propria lymphocytes in hematoxylin and eosin-stained small intestinal biopsies from cats. The median sensitivity, positive predictive value, and F1 score of the AI model compared with the majority opinion of 11 veterinary anatomic pathologists, were 100% (interquartile range [IQR] 67%-100%), 57% (IQR 38%-83%), and 67% (IQR 43%-80%) for intraepithelial lymphocytes, and 89% (IQR 71%-100%), 67% (IQR 50%-82%), and 70% (IQR 43%-80%) for lamina propria lymphocytes, respectively. Errors included false negatives in whole-slide images with faded stain and false positives in misidentifying enterocyte nuclei. Semiquantitative grading at the whole-slide level showed low interobserver agreement among pathologists, underscoring the need for a reproducible quantitative approach. While semiquantitative grade and AI-derived lymphocyte counts correlated positively, the AI-derived lymphocyte counts overlapped between different grades. Our AI model, when supervised by a pathologist, offers a reproducible, objective, and quantitative assessment of feline intestinal lymphocytes at the whole-slide level, and has the potential to enhance diagnostic accuracy and consistency for feline chronic enteropathy., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.