Chapter 6
Heritability estimations of diseases, coat color, body weight
and height in a birth cohort of Boxer dogs.
A.L.J Nielen1, L.L.G. Janss2 and B.W. Knol1
1 Department of Clinical Sciences of Companion Animals, P.O. Box 80154, 3508 TD
Utrecht, The Netherlands
2 Institute for Animal Science and Health (ID-Lelystad) P.O. Box 62, 8200 AB Lelystad, The
Netherlands
Submitted to American Journal of Veterinary Research
2
Summary
Objective: Heritability estimations of diseases and animal characteristics in boxer dogs using
different models as a basis for the development of genetic counseling programs.
Animals: A birth cohort of 2929 pure bred boxer dogs from 414 litters.
Procedure: Heritabilities were estimated for cheilo/palatoschizis, cryptorchism, epilepsy (two
definitions), knee disorders (two definitions), heart disorders (three definitions), white coat
color, birth weight, adult weight and shoulder height. All traits were analyzed with a mixed
effects probit model; some traits were also analyzed with a model postulating a monogenic
inheritance. The variation in disease incidences between clusters of related animals was
studied.
Results: Heritability was virtually none for heart disorders, medium (0.17 to 0.36) for most
other traits and high (>0.55) for coat color white, birth weight (but not adult weight) and
height. Common environment for full sibs and risk factors notably affected
cheilo/palatoschizis, heart murmur, epilepsy (in a broad definition, but not in a narrow
definition) and adult weight. Heritabilities increased if stricter definitions for epilepsy and knee
disorders were used. The monogenic model did not show higher heritabilities than the probit
model, for six of the traits analyzed. White color showed the most significant different clusters
(n=10). In most traits, there was a strong relation between the average breeding value per
cluster and the prevalence in these clusters.
Conclusions: The results indicate that genetic improvement of most of these traits should be
feasible except for heart disorders. However, as most of these traits were found to be
influenced by environmental effects as well, genetic counseling methods using family
information is preferred to strict exclusion of parents.
3
Introduction
Hereditary diseases are a major concern of the present purebred dog breeders.1-2 Therefore,
screening programs have been developed and breeding rules were formulated for several
breeds. Selection in dog breeding, to reduce disease frequency, is mainly based on exclusion of
patients as parents or of parents with an undesired phenotype, for example in hip dysplasia. 3-6
However, exclusion of affected parents from breeding is not necessarily effective. Firstly, if the
disease is not heritable. Secondly, if the disease is multifactorial, for obvious reasons, exclusion
of affected parents may be a relatively inefficient, crude or arbitrary measure. Exclusion of
affected parents may thus lead to (unnecessary or too large) narrowing of the population, and
thus to extra inbreeding.7
Heritability is an important predictor of the success of selection, because heritability expresses
the reliability of the phenotypic value as a guide to the breeding value.8 Heritability and
breeding values can be estimated in different models. The probit model, very similar to a
logistic model, was suggested by Wright to describe polygenic inheritance for a certain discrete
trait.9 Probit (or similar) models allow to include environmental cofactors and random effects
for common environment of full sibs and are therefore considered particularly suited for the
investigation of multifactorial diseases and as a basis for genetic counseling for multifactorial
diseases.10 To estimate heritability of a single-gene disorder other models were developed.11
Another way to investigate family aspects of diseases is the estimation of relative risks for
diseases in clusters of related animals.12-13 An advantage of this method, cluster analysis, is, that
no assumptions are needed about the pattern of inheritance, but at the other hand it is less
suited for multifactorial diseases, because it can not adjust for environmental effects.
The aim of this report is to perform a first study of the heredity of several diseases and of some
general characteristics based on survey data in Dutch boxer dogs. Investigated diseases were
4
selected, because a genetic background was known from literature or was assumed by boxer
breeders and boxer owners.14-24 Heritabilities will be estimated using various models and will
be compared with results from cluster analysis. The quality and usefulness of the survey data
for heritability estimation will be discussed.
Materials and methods
Population
Data were collected from litters of the boxer population born in the Netherlands between
January 1994 and March 1995. All dams had an official pedigree from the Dutch Kennel Club.
All sires were registered in FCI (Fédération Cynologique Internationale) enlisted Kennel Club
registration. In total 457 litters were born in that period and information was collected from
414 litters with 2629 pups.25 Breeders gave information about mortality, diseases and other
problems until the pups went to their new owners. Also information about ancestry and the
environmental situation in which the litter was raised was collected in this study period. The
breeders received a note-book (Diary of the Boxer) for each pup. In this book information
about the dog's health and preventive treatments could be collected. It also contained the
objectives and methods of this study. The breeder forwarded these books to the new owners.
After weaning age, we separated the dogs in two cohorts. One dog from each litter was
randomly chosen to be in the cohort that was monitored by telephone. All other pups were
monitored by written questionnaires. Interviews and questionnaires were carried out every six
months, starting at an age of six months, until February 1998. At this time, the oldest dogs
were about four years old and the youngest dogs three years old. Data about survival, diseases
and disorders of each half year were collected in these interviews.
5
Diseases and animal characteristics (traits)
The following diseases were analyzed in this study:
- Cheilo: Dogs with cheiloschizis, palatoschizis or cheilopalatoschizis. The diagnosis was made
by breeders, veterinarians or at postmortem examination.
- Cryptorchism: Canine cryptorchism was diagnosed by owners and/or veterinarians. We
made no distinction between unilateral and bilateral cryptorchism.
- Epilepsy: Dogs with seizures diagnosed by owners or veterinarians were assumed to suffer
from epilepsy and were classified as “Epilepsy” cases. When a dog displayed severe seizures
more than once and the veterinarian diagnosed an idiopathic form of canine epilepsy or the
dog showed a status epilepticus, the dog was additionally classified as “Severe epilepsy” case.
- Knee: A dog was lame in one or both hind leg(s) and a veterinarian diagnosed (by clinical
investigation) knee problems. When further diagnostic work revealed cranial cruciate ligament
rupture, fractured or ruptured meniscus, severe osteo-arthrosis of the knee, or a combination
of these disorders, the dog was additionally a case in the trait “Severe knee”.
- Heart: We distinguished three levels of heart-disorders. When the dogs were four years old,
we asked whether or not the veterinarian had auscultated the heart of the dog (at any age). If
an abnormal heart sound was heard, the dog was a case in the trait “Heart murmur”. When
further diagnostics were performed and there was ample evidence that there was a heart
abnormality, the dog was additionally a case in the trait “Heart abnormalities”. This category
contains accurately diagnosed abnormalities such as aortic stenosis and pulmonary stenosis as
well as less certain diagnoses. For example: radiographic examination revealed an enlarged
heart and a systolic murmur was heard, but no further diagnostics were performed. When an
aortic stenosis was diagnosed with echocardiography or on postmortem examination, the dog
was also a case in the trait “Aortic stenosis”.
6
The next animal characteristics were analyzed in this study:
- White: White coat colored boxers with or without spots of fawn or brindle on them.
- Weight: Birth weight was determined on the day of birth and registered by the breeder. The
owners registered Adult weight for this study at an age between 2.5 and 3.5 years. Average
weight and standard deviation were calculated in the pooled cohorts.
- Height: Shoulder height was measured at the withers at an age between 2.5 and 3.5 years,
only of dogs of the cohort monitored telephonically. Average height and standard deviation
were calculated.
Traits were either binomial (yes/no, presence/absence) or continuous (Weight and Height).
Pedigree
Ancestral data of the birth cohort was traced in records of the Dutch Kennel Club and merged
with a second computerized data set.26
Statistical methods
Prevalences of binomial traits were calculated by dividing the number of cases by the total
number of cases and non cases (so missing cases were not included in the denominator). Mean
and standard deviation of the continuous traits Weight and Height were calculated using SPSS
(SPSS for windows, release 9.0).
Heritability estimation: probit model
To estimate heritability in a probit model, a software was used based on Janss and Foulley.27
The theoretical basis of the model used, and algorithms applied are described by Gianola and
Foulley and Janss and Foulley.27-28 Variance estimation is based on an EM-REML algorithm.27
7
In the probit model, all effects of parents are modeled as random effects and the variance
component estimated for the parental effects is used to compute heritability of the trait. Three
different estimates of heritability were performed. Firstly, heritability was estimated in a model
were only the disease status and the pedigree were included. In a second model the litter was
also included (as random effect), to correct for maternal effects and common environment for
litter mates, during pregnancy and weaning period. The third model included the disease
status, the pedigree, the litter (as a random effect) and known or suspected risk factors from
literature (as fixed effects).
Heritability estimation: Single gene model
A monogenic model (bi-allelic, autosomal) was fitted using a Monte Carlo Markov Chain
(MCMC) algorithm. A relaxation technique, and blocked sampling of genotypes was used to
improve convergence. 29-30 For some analyses two levels of relaxation appeared to be required
for proper convergence, implemented as with the simulated tempering sampler of Geyer and
Thompson.31 Using the notation of Falconer, the 3 genotypes for this model are aa, Aa and
AA, with frequencies in the founder population of q2, 2pq and p2, assuming Hardy-Weinberg
proportions.8 The penetrance functions, the probabilities of sickness given a certain genotype,
we have denote as λaa, λAa and λAA. The restrictions λaa > λAa and λaa > λAA were applied, so that
aa will be the genotype with the highest probability of sickness and q is the frequency of the
putative disease allele. The MCMC scheme of Sheehan and Thomas was extended to estimate
the model parameters (q, λaa, λAa, λAA) in a Bayesian way, by adding to the MCMC the
sampling of these parameters from beta distributions with flat priors.29-30 For estimation of
parameters, repeated Markov chains of 200000 cycles were generated, until a minimum of 100
independent samples for all parameters was obtained, judged by comparison of within- and
8
between chain variances.11 Heritabilities for the monogenic model were computed on an
underlying probit scale, using the inverse probit function to transform penetrance probabilities
to genotype means on the probit scale and subsequently computing the variance of genotype
means. A broad sense heritability (“total”, including dominance variance) and a narrow sense
heritability (additive variance only) were computed.
Genetic cluster analysis
To group the boxers into clusters of related dogs (relatedness > 0.125) a hierarchal cluster
analysis with average-linkage-between-clusters was applied on a matrix of relatedness between
all dogs of the birth cohort.13 Of all binomial traits, prevalences were calculated per cluster and
the relative risk (RR) of a cluster, relative to the total cohort, was calculated using: RRcluster =
Pcluster / Pbirthcohort. In this formula Pcluster is the prevalence of a trait in the cluster, the Pbirthcohort is the
prevalence of the trait in the total birth cohort. The 95 % confidence intervals (CI) of these
RR were calculated using: CI min = e ln(RR) - 1.96 √var [ln(RR)] and CI max = e ln(RR) + 1.96 √var [ln(RR)].32 Clusters
with confidence intervals of the RR with a minimum value higher than 1 or a maximum
value lower than 1, were considered significantly different from the total population.
We calculated the correlation coefficient of the prevalence of clusters of each trait and the
average breeding value of clusters. Scatter plots of the prevalence and average breeding value
of high, average and low correlations were created. Breeding values of the dogs in the birth
cohort were obtained as the average breeding value of each dog’s parents, where the latter
were available from the probit model.
9
Results
The mean birth weight of 1705 pups was 486 grams (sd 84). Average adult weight in 1163
boxers was 31.66 kilogram (sd 5.05). The shoulder height was only measured by owners
participating in “the telephonic cohort” and the average height of 210 boxers was 60.67
centimeter (sd 4.81).
Cryptorchism had a prevalence of 10.7% and this was the highest prevalence of all traits
included in this study. Other traits with prevalences higher than 5 were Heart murmur (9.7%)
and White (8.7%). A mortality rate of 100% was found in Cheilo. Epilepsy (40.8%), Severe
epilepsy (55.8%), Aortic stenosis (41.7%) and White (44.9%) showed also high percentages of
mortality (Table 1).
Estimates of the heritability are figured in Table 2 and Table 3. Birth weight (h2 corrected =
0.62), White (h2 = 0.61) and Height (h2 = 0.53) showed high heritabilities in the probit
model. In the single gene model White had a high heritability (h2 additive = 0.34).
Heritability estimates decreased for the disorders Knee and Epilepsy when not only cases with
an accurate diagnosis were included, but also less certain cases. In most traits, heritability
decreased when corrected for litter and risk factors. Only Birth weight showed a considerable
increase. All heart disorders showed low heritability estimates.
Confidence intervals of relative risks of traits in most genetic clusters included one, so
prevalences of these traits in these clusters were not significantly lower or higher than in the
total population. White had the most significant different clusters, namely 10 clusters. The
other traits had 0 to 3 clusters with significant lower or higher prevalences (Figure 1).
The strength of the relations (Table 4) between the average breeding value of a trait per
cluster and the prevalence of this trait per cluster was high in most traits (correlation
coefficient was between 0.7 and 0.89). Cryptorchism, Epilepsy (all cases) and knee (all cases)
10
showed lower correlation coefficients (Table 4). Some examples of scatter plots of prevalences
and average breeding values of clusters illustrate the differences in correlation (Figure 2).
Discussion
In this study the heritability of diseases, coat color white, weight and height was estimated in a
birth cohort of 2629 boxers. Prevalences of diseases and White, up to four years of age, were
between 1.7% (Severe epilepsy) and 10.7% (Cryptorchism). Up to four years of age, the
prevalence of some traits, for example Severe epilepsy and Aortic stenosis, was not high
(respectively 1.7% and 1.3%), but mortality was high (respectively 55.8% and 41.7%). The
high mortality rates of 100% for Cheilo and 44.9 for White were mainly caused by the
breeders’ decisions to euthanase pups with cheiloschizis, palatoschizis or cheilopalatoschizis or
a white coat color.
Although we didn’t have complete pedigrees of all boxers of the birth cohort, in the fifth
generation 85% of the ancestors was known.33 Therefore, we considered the quality of these
data to be good enough to estimate an accurate relatedness between the boxers in the birth
cohort.13
In general, the results showed medium to high heritabilities with most diseases in the medium
range and White, Birth Weight and Height in the high range. Only Heart traits showed very
low to virtually absent heritabilities. Different models altered little to the general conclusions.
Inclusion of permanent environmental effects for full sibs and of additional risk factors notably
affected Cheilo, Epilepsy and Adult Weight. Monogenic models showed generally lower
heritabilities, such that for none of the traits investigated a monogenic model appears plausible.
The clustering procedure also indicated White to have a clear association with familial lines;
White was found the most heritable trait in the probit model. Average cluster breeding values
11
and cluster incidences showed a good correspondence, except for Cryptorchism and Epilepsy.
This suggests that the additive model of inheritance could be incorrect. Because Epilepsy and
Knee-problems are very likely a mixture of diagnoses, low correlation coefficients in these
traits could be possible. Some studies on cryptorchism disagree about the mode of
inheritance.16,34 Because of this disagreement in both literature and in this study, more research
into the genetic aspects is suggested, before starting genetic counseling of cryptorchism. For
example, by separating maternal and paternal contributions to the inheritance as done by Janss
and Brascamp.35 The accuracy of heritability estimations could be evaluated in the monogenic
models and yielded standard errors of heritabilities around 0.10. The single gene model
estimated heritability in the broad sense (h2 total) and in the narrow sense (h2 additive). Which
of the estimations is to be used, depends on the goal for which the estimated heritability is
used. The additive genetic component is most useful for genetic counseling, because it
determines the degree of resemblance between parents and offspring.8
Cheiloschizis, palatoschizis or cheilopalatoschizis in other studies are described as having a
genetic background, although the mode of inheritance differs in the studies.15, 17, 36-39
The relatively high heritability of epilepsy, although not as high as Famula found in Belgian
Tervueren, is interesting , because epilepsy in boxers is often severe and it was the disorder
with the highest mortality rate in Boxers between weaning age and four years (Nielen 1999,
unpublished data). In a few recent studies, in different breeds the genetic background of a dog
is a major risk factor of epilepsy.21, 23, 40-43 The high heritability level suggests that genetic
counseling, based on the breeding values, found in the same models that are used in this study
to estimate heritability 27-28, can help to select parents in such a way that the prevalence of
epilepsy will decrease.44
12
Estimations of heritability of Knee-problems were performed in two ways: proved knee-
problems and proved or suspected knee-problems. For both traits we corrected the known
risk factors, because next to breed, also body weight, age, and sex were known as risk
factors.19, 45-50 The heritability of the proved cases was much higher than the heritability of the
proved and suspected cases (respectively 0.28 and 0.15 in the probit model). Therefore it is
very likely that improved diagnostics on Knee-problems, will be useful to increase the results
of genetic counseling.
All three cardiac traits had low heritability estimations in all models (varying from 0.00 to
0.09). In more studies the occurrence of heart abnormalities differed between breeds 20, 22, 51
and this is often considered an indication for diseases to have a major genetic background.52
Our finding does not subscribe these findings. Therefore, we suggest that, in the next four
years of this boxer follow up study cardiac problems will have extra attention.
According to literature, the genotype of white colored boxers is swsw and this s-locus is the only
locus responsible for extensive white in Boxers.14,24 Assuming a monogenic inheritance with a
complete dominance, a Hardy-Weinberg equilibrium and a prevalence of 0.087 (the
prevalence for White in this study), an additive heritability of 0.46 is expected.8 In that case
the remaining variance should be the dominance variation. We found an (additive) heritability
of 0.61 in the probit model, so based on this result, a monogenic, complete dominance trait is
possible. However, the single- gene model did not support this assumption. In this model a
total heritability (additive and dominance) of 1.0 is expected, with the same assumptions as
mentioned above. However, we estimated a heritability of 0.53 and also the 90% confidence
intervals did not include 1.0. Two explanations for this finding are possible. First, the
assumption of monogenic inheritance, with complete dominance may not be correct. Second,
the phenotyping is maybe incomplete, because not all cases were reported. Fifty percent of the
13
white boxer pups were euthanased immediately after birth. Breeders easily could withhold this
information. In another study of this boxer cohort this lack of information was not confirmed,
however.25
Knowledge of the heritability is useful in genetic counseling for calculating recurrent risks in
families because it allows all the information about the family to be combined correctly.
Individual selection of disorders with a binomial distribution is mainly based on the prevalence
of the disorder, whereas in continuous characters the proportion of selected ancestors is more
important.8 In rare diseases and disorders with a low heritability, family selection will be more
efficient than individual selection.8, 53 Defining families in purebred dog population is
complicated and therefore we used a method which assigns related dogs to a cluster.13
Differences in prevalence of traits between clusters would give information about the
distribution of a trait in the population, while breeding values of animals within clusters could
be useful in selecting parents for mating.
In conclusion, several traits show medium-high heritabilities (20% and more), which indicates
good prospects for change by selection. This applies notably to Cryptorchism, Severe epilepsy,
Severe knee and white coat color. These traits also show relatively small influences of litter
effects and other risk factors on the estimate of heritability. Other traits have lower
heritabilities and/or are clearly influenced by non-genetic effects, e.g. Cheilo and Epilepsy and
Knee with a more liberal definition. In general these traits appear multifactorial and genetic
counseling therefore is best based on models that allow inclusion of additional explaining
effects and risk terms, such as the probit model applied here. This study also shows that data
collection by questionnaires supplies data of sufficient quality for genetic counseling.
Acknowledgments
14
This study would not have been possible without the cooperation of the breeders. We greatly
appreciate their efforts. The support of the Ministry of Agriculture, Nature Management and
Fisheries, the Dutch Kennel Club, and the Dutch Boxer Club was essential for the completion
of the project.
We like to thank prof. dr. B.A.van Oost and prof. dr. ir. E.W. Brascamp for critically reading
the manuscript.
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17
Table 1: Number of cases, non-cases, prevalences and mortality in a birth cohort of 2629 boxers. Traits
Cases
Non-cases
Prevalence1
Dead or
euthanased
Mortality
of cases (%) Cheilo
61
2561
2.3
61
100.0
Cryptorchism2
80
667
10.7
0
0.0
Epilepsy
49
1984
2.4
20
40.8
Severe epilepsy
34
1984
1.7
19
55.8
Knee
117
1932
5.7
2
1.7
Severe knee
59
1933
3.0
1
1.7
Heart murmur
200
1852
9.7
22
11.0
Heart abnormalities
55
1852
2.9
9
16.4
Aortic stenosis
24
1852
1.3
10
41.7
White
227
2333
8.7
102
44.9
1 Prevalence: Cases as a percentage of the non-cases plus cases. Boxers with missing data (e.g. a male dog that died during the first week) were excluded in this prevalence calculation. 2 Prevalence was calculated using males exclusively.
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Table 2: Heritability (h2) in a probit model in a birth cohort of 2629 boxers. Traits
risk factor1
h2
h2 (corrected for litter)2
h2 (corrected for litter and risk factors)
Cheilo
-
0.27
0.17
n.a.3
Cryptorchism
-
0.24
0.23
n.a.3
Epilepsy
sex
0.11
0.01
0.08
Severe epilepsy
sex
0.36
0.34
0.33
Knee
adult
weight
0.15
0.15
0.16
Severe knee
adult
weight
0.28
0.27
0.28
Heart murmur
sex
0.04
0.00
0.00
Heart abnormalities
sex
0.01
0.00
0.00
Aortic stenosis
sex
0.00
0.00
0.00
White
-
0.61
n.a.3
n.a.3
Birth weight
sex
litter size
0.55
0.54
0.62
Adult weight
litter size neutered height
0.18
0.08
0.04
Height
-
0.53
n.a.3
n.a.3
1 Risk factors that are known from literature to be possibly related to a trait. The heritability is corrected for these risk factors in the last column (as fixed effect in the model). 2 Dogs in one litter shared the same environment during gestation time and the first weeks of life. Less variance between litter mates than between dogs from different litters is to be expected. Therefore, heritability was corrected for litters (as random effect in the model). 3 n.a.: Not analyzed, because there were no risk factors for these traits involved in this study.
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Table 3. Heritability (h2) of traits in a single gene-model in a birth cohort of 2629 boxers. Traits
h2 total 1
SD 2
90 % CI 3
h2 additive 4
SD 2
90 % CI 3
Cheilo
0.17
0.10
0.00 - 0.59
0.09
0.09
0.00 - 0.55
Cryptorchism
0.22
0.14
0.00 - 0.74
0.11
0.09
0.00 - 0.53
Epilepsy
0.18
0.10
0.00 - 0.59
0.10
0.09
0.00 - 0.49
Severe epilepsy
0.21
0.10
0.02 - 0.61
0.14
0.11
0.00 - 0.57
Aortic stenosis
0.09
0.09
0.00 - 0.56
0.04
0.05
0.00 - 0.51
White
0.53
0.08
0.22 - 0.78
0.34
0.12
0.00 - 0.70
1 Heritability in the broad sense: the total genetic variance divided by the phenotypic variance. 2 Standard deviation. 3 Ninety percent confidence interval. 4 Heritability in the narrow sense: the additive genetic variance divided by the phenotypic variance.
20
Figure 1. Numbers of cases of the binomial traits in clusters1 of related boxers (relatedness >0.125). Each vertical line hitting the x-axis (0.125 relation coefficient) represents a cluster. The upper part of the y-axis represents the level of relatedness between clusters. In the lower part of the y-axis, the number of boxers per cluster, the number of cases per cluster and the total numbers of cases per trait (between brackets) are figured. Clusters with 95% confidence intervals of the RR with a minimum value higher than 1 or a maximum value lower than 1, were considered significantly different from the total population. (*: RR was significantly higher than 1, **: RR was significantly lower than 1).
1 To group the boxers into clusters of related dogs (relatedness > 0.125) a hierarchal cluster analysis was performed using the estimated genetic similarity of all pair-wise combined dogs.13
21
Table 4. Correlation coefficients (r) of the prevalence of a trait per cluster and the average breeding value of this trait per cluster. The average breeding values were calculated in the probit models with and without correction for litter and risk factors. Traits
Corrected
for litter
Corrected for litter
and risk factors
r
r
r
Cheilo
0.735
0.718
n.a.1
Cryptorchism
- 0.053
- 0.052
n.a.1
Epilepsy
- 0.168
- 0.137
- 0.169
Severe epilepsy
0.839
0.837
0.828
Knee
0.466
0.464
0.458
Severe knee
0.745
0.740
0.731
Heart murmur
0.774
0.716
0.691
Heart abnormalities
0.727
0.724
0.717
Aortic stenosis
0.747
0.750
0.739
White
0.813
0.730
n.a.1
1 n.a.: Not analyzed, because there were no risk factors for these traits involved in this study.
22
Figure 2. Scatter plots of prevalence and average breeding values in clusters. To group the boxers into clusters of related dogs (relatedness > 0.125) a hierarchal cluster analysis was performed using the estimated genetic similarity of all pair-wise combined dogs.13 Plots of the traits White, Cryptorchism, Epilepsy and Knee were figured as example for high, average and low correlations.
