Using Bronson Equation to Accurately Predict the Dog Brain Weight Based on Body Weight Parameter

Estimating the heritability of cognitive traits across dog breeds reveals highly heritable inhibitory control and communication factors

Trait heritability is necessary for evolution by both natural and artificial selection, yet we know little about the heritability of cognitive traits. Domestic dogs are a valuable study system for questions regarding the evolution of phenotypic diversity due to their extraordinary intraspecific variation. While previous studies have investigated morphological and behavioral variation across dog breeds, few studies have systematically assessed breed differences in cognition. We integrated data from Dognition.com-a citizen science project on dog cognition-with breed-averaged genetic data from published sources to estimate the among-breed heritability of cognitive traits using mixed models. The resulting dataset included 11 cognitive measures for 1508 adult dogs across 36 breeds. A factor analysis yielded four factors interpreted as reflecting inhibitory control, communication, memory, and physical reasoning. Narrow-sense among-breed heritability estimates-reflecting the proportion of cognitive variance attributable to additive genetic variation-revealed that scores on the inhibitory control and communication factors were highly heritable (inhibitory control: h² = 0.70; communication: h² = 0.39), while memory and physical reasoning were less heritable (memory: h² = 0.17; physical reasoning: h² = 0.21). Although the heritability of inhibitory control is partially explained by body weight, controlling for breed-average weight still yields a high heritability estimate (h² = 0.50), while other factors are minimally affected. Our results indicate that cognitive phenotypes in dogs covary with breed relatedness and suggest that cognitive traits have strong potential to undergo selection. The highest heritabilities were observed for inhibitory control and communication, both of which are hypothesized to have been altered by domestication.

Leveraging brain-body scaling relationships for comparative studies

In Horschler et al. (Anim Cognit 22(2):187-198, 2019), we found that two components of executive function (short-term memory and self-control) were strongly associated with estimated absolute brain weight across dog breeds, and argued that dogs present a powerful model for studying evolutionary links between cognition and neuroanatomy due to their extraordinary degree of intraspecific morphological variation. In a commentary on this work, Montgomery (Anim Cognit, 2019) raises concerns about the practice of estimating brain weights from brain-body scaling relationships. Montgomery explores the practical significance of this approach, ultimately concluding that such estimations should be avoided. In this response, we point out some limitations of the analyses presented by Montgomery and consider his conclusions in light of these issues. We then explore the extent to which body weight serves as a valid proxy for brain weight under varying conditions. Through simulations, we show that the consequences of using body weight as a proxy for brain weight depend on parameters including effect size, the correlation between brain and body weight, and the variance in brain and body weight within a sample. Under conditions approximating those in Horschler et al. (Anim Cognit 22(2):187-198, 2019), we find that body weight is a reliable proxy for brain weight, and that statistical results from models using either brain weight or body weight as predictor variables are highly convergent. Nonetheless, we wholeheartedly agree with Montgomery that empirical data on brain weight, structure, and cellular composition will be critical for creating new opportunities to investigate the relationships between neuroanatomy and cognition in dogs.

Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing

Structural ‘brain age’ is a valuable but complex biomarker for several brain disorders. The dog is an unrivalled comparator for neurological disease modeling, however canine brain morphometric diversity creates computational and statistical challenges. Using a data-driven approach, we explored complex interactions between patient metadata, brain morphometry, and neurological disease. Twenty-four morphometric parameters measured from 286 canine brain magnetic resonance imaging scans were combined with clinical parameters to generate 9,438 data points. Network analysis was used to cluster patients according to their brain morphometry profiles. An ‘aged-brain’ profile, defined by a small brain width and volume combined with ventriculomegaly, was revealed in the Boxer breed. Key features of this profile were paralleled in neutered female dogs which, relative to un-neutered females, had an 11-fold greater risk of developing brain tumours. Boxer dog and geriatric dog groups were both enriched for brain tumour diagnoses, despite a lack of geriatric Boxers within the cohort. Our findings suggest that advanced brain ageing enhances brain tumour risk in dogs and may be influenced by oestrogen deficiency—a risk factor for dementia and brain tumours in humans. Morphometric features of brain ageing in dogs, like humans, might better predict neurological disease risk than patient chronological age.