Study Design Retrospective study of male and female spinal osteoarthritis, characterized by lateral spine thoracolumbar radiographs, in humans and nonhuman primates Objective To characterize differences in prevalence and vertebral distribution of spinal osteoarthritis between men and women, between male and female macaques, and between the two phylogenetically related genera. Summary of Background Data Naturally occurring spinal osteoarthritis manifests similarly in humans and rhesus macaques. Other types of osteoarthritis particularly of the knee and hip have revealed gender differences in humans. In regard to spinal osteoarthritis, gender differences have been noted but without consistent results. Sex differences in macaques have not been examined. Methods Radiographic evidence of disc space narrowing and osteophytosis was assessed using an atlas scoring method. Prevalence was determined according to sex, age, body mass (for macaques only) and spinal location (human T4-L5; macaque T8-L7). Results Average scores in macaques differed between the sexes, but they did not differ between men and women. The pattern of involvement along the spine was the same in male and female monkeys but differed between men and women: women had more thoracic involvement and men had more lumbar involvement. Overall, monkeys had a significantly higher prevalence of osteoarthritis than humans. Conclusion The appearance of sex differences in the prevalence of osteoarthritis is most likely a proxy measure for the affect of body mass. Sex differences were apparent in monkeys due to the fact that males are significantly heavier than females. No gender difference in prevalence was apparent in humans and there is substantial overlap in body mass between men and women. Differences in the location of osteoarthritic involvement along the spine between men and women were obscured when only average scores were examined.

Cross-sectional analyses of naturally-occurring spinal osteoarthritis (OA) in primates have shown that age and body mass are significant predictors, but whether or not these relationships hold true in longitudinal evaluations remains unclear. Because spinal OA manifests similarly in humans and monkeys and macaque monkeys age > 3 times the rate of humans, macaque models offer opportunities for longitudinal study that are difficult in humans. Our objective was to characterize the longitudinal development over 11 years of spinal OA in 68 Macaca mulatta (41 males, 27 females, aged 11-32 years). Average disc space narrowing (DSN) and osteophytosis (OST) scores were computed for the thoracolumbar spine (T8-L7). Our longitudinal analyses confirmed the cross-sectional results: age and body mass (p <0.001) significantly predicted 50% and 39% of the variability in OST and DSN, respectively. Rates of change in DSN, but not OST, were associated with age at first radiograph. This study represents the first long-term longitudinal assessment of OA in primates and establishes that the relationship among the covariates in the cross-sectional and longitudinal approaches is similar.

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We examine heritability estimation of an ordinal trait for osteoarthritis, using a population of pig-tailed macaques from the Washington National Primate Research Center (WaNPRC). This estimation is non-trivial, as the data consist of ordinal measurements on 16 intervertebral spaces throughout each macaque’s spinal cord, with many missing values. We examine the resulting heritability estimates from different model choices, and also perform a simulation study to compare the performance of heritability estimation with these different models under specific known parameter values. Under both the real data analysis and the simulation study, we find that heritability estimates from an assumption of normality of the trait differ greatly from those of ordered probit regression, which considers the ordinality of the trait. This finding indicates that some caution should be observed regarding model selection when estimating heritability of an ordinal quantity. Furthermore, we find evidence that our real data have little information for valid heritability estimation under ordered probit regression. We thus conclude with an exploration of sample size requirements for heritability estimation under this model. For an ordinal trait, an incorrect assumption of normality can lead to severely biased heritability estimation. Sample size requirements for heritability estimation of an ordinal trait under the threshold model depends on the pedigree structure, trait distribution and the degree of relatedness between each phenotyped individual. Our sample of 173 monkeys did not have enough information from which to estimate heritability, but estimable heritability can be obtained with as few as 180 related individuals under certain scenarios examined here.

We examine heritability estimation of an ordinal trait for osteoarthritis, using a population of pig-tailed macaques from the Washington National Primate Research Center (WaNPRC). This estimation is non-trivial, as the data consist of ordinal measurements on 16 intervertebral spaces throughout each macaque's spinal cord, with many missing values. We examine the resulting heritability estimates from different model choices, and also perform a simulation study to compare the performance of heritability estimation with these different models under specific known parameter values. Under both the real data analysis and the simulation study, we find that heritability estimates from an assumption of normality of the trait differ greatly from those of ordered probit regression, which considers the ordinality of the trait. This finding indicates that some caution should be observed regarding model selection when estimating heritability of an ordinal quantity. Furthermore, w e find evidence that our real data have little information for valid heritability estimation under ordered probit regression. We thus conclude with an exploration of sample size requirements for heritability estimation under this model. For an ordinal trait, an incorrect assumption of normality can lead to severely biased heritability estimation. Sample size requirements for heritability estimation of an ordinal trait under the threshold model depends on the pedigree structure, trait distribution and the degree of relatedness between each phenotyped individual. Our sample of 173 monkeys did not have enough information from which to estimate heritability, but estimable heritability can be obtained with as few as 180 related individuals under certain scenarios examined here.