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Häggström, J.

Publications and source records attributed to Häggström, J..

4 recordsLinked to original sources

Reproducibility of the evaluation of genetic variant pathogenicity based on the animal variant classification guidelines

Until recently, due to the absence of standardized guidelines tailored for veterinary use, the evaluation of genetic variant pathogenicity for single-gene diseases was based on a personal interpretation of the presented evidence, which has led to ambiguous interpretation. With the publication of the animal variant classification guidelines (AVCG), a more objective approach became available. Variants are evaluated based on twenty-three criteria and labeled as pathogenic, likely pathogenic, variant of uncertain significance, likely benign or benign. While the accuracy was thoroughly tested in the original publication, the reproducibility of the various steps involved was only briefly checked, which is why the current study was performed. Each variant from a set of 150 published likely causal variants for single-gene diseases from three species (dog, cat, horse) was independently and blindly assessed by three different reviewers, each applying the same AVCG. An overall agreement of 93% for decisions on the scope, i.e. whether they fit the inclusion criteria to allow evaluation with AVCG, was found. More importantly, the reproducibility was 65% for the pathogenicity classification and this increased to 83% clinically relevant agreement. While a direct comparison of the reproducibility with human literature is not possible for the scope, the reproducibility on pathogenicity classification is in line with reports using the human American College for Medical Genetics and Genomics and Association for Molecular Pathology guidelines for human variants. Overall, based on the current study, the reproducibility of the guidelines in veterinary species is within current expectations.

genetics↗

Variant classification guidelines for animals to objectively evaluate genetic variant pathogenicity

Assessing the pathogenicity of a disease-associated variant in animals accurately is vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect exclusion of animals and compromise the long- term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. Criteria to determine pathogenicity are not standardized, hence no guidelines for animal variants are available. Here, we developed and optimized the animal variant classification guidelines, based on those developed for humans by The American College of Medical Genetics and Genomics, and demonstrated a superior classification in animals. We described methods to develop datasets for benchmarking the criteria and identified the most optimal in silico variant effect predictor tools. As the reproducibility was high, we classified 72 known disease-associated variants in cats and 40 other disease-associated variants in eight additional species.

genetics↗

Body condition score and triglyceride concentrations and their associations with other markers of energy homeostasis in healthy, non-obese dogs

Serum triglyceride concentrations increase in dogs in overweight condition, which is typically assessed by body condition score (BCS). However, their associations with other markers of energy homeostasis are poorly characterized. The present study aimed to evaluate the associations between both BCS and triglyceride levels and other markers of lipid and glucose metabolism in healthy dogs in overweight condition. 534 overweight, but otherwise healthy, client-owned dogs were included. Serum concentrations of cholesterol, free fatty acids, triglycerides, insulin, glucose and fructosamine were measured. Dogs were assigned to lean (BCS: 3-5) or overweight (BCS: 6-7) categories, and linear models were used to assess the differences between BCS categories and the associations between triglycerides and the other variables, correcting for the effect of breed. Globally, "overweight" dogs had greater serum cholesterol (95% CI: 5.3-6.2 mmol/L or 205-237 mg/dL versus 5.1-5.4 mmol/L or 198-210 mg/dl, P = .003), insulin (95% CI: 17.5-22.1 U/ml versus 16.7-18.0 U/ml, P = .036) and were older (95% CI: 4.0-5.3 versus 3.4-3.7 years, P = .002) than lean dogs. Triglyceride concentrations were positively associated with fructosamine (r2 = 0.31, P = .001), cholesterol (r2 = 0.25, P < .001), insulin (r2 = 0.14, P = .003) and glucose (r2 = 0.10, P = .002), and negatively associated with free fatty acids (r2 = 0.11, P < .001). There was no association between triglyceride levels and age. In conclusion, both BCS and triglyceride concentrations were associated with other markers of glucose and lipid metabolism in overweight, but otherwise healthy dogs. Triglyceride concentrations were associated with an increase in insulin and fructosamine that might reflect an early-phase impairment in glucose tolerance which, surprisingly, was concurrent with lower basal free fatty acids.

physiology↗

Properties of the full random effect modelling approach with missing covariates

Two full model approaches was compared with respect to their ability to handle missing covariate information. The reference data analysis approach was the full model method in which the covariate effects are estimated conventionally using fixed effects, and missing covariate data is imputed with the median of the non-missing covariate information. This approach was compared to a novel full model method which treats the covariate data as observed data and estimates the covariates as random effects. A consequence of this way of handling the covariates is that no covariate imputation is required and that any missingness in the covariates is handled implicitly. The comparison between the two analysis methods was based on simulated data from a model of height for age z-scores as a function of age. Data was simulated with increasing degrees of randomly missing covariate information (0-90%) and analyzed using each of the two analysis approaches. Not surprisingly, the precision in the parameter estimates from both methods decreased with increasing degrees of missing covariate information. However, while the bias in the parameter estimates increased in a similar fashion for the reference method, the full random effects approach provided unbiased estimates for all degrees of covariate missingness.

epidemiology↗