Evaluating individual biomarkers for predicting health risks in zoo-housed chimpanzees (Pan troglodytes) and bonobos (Pan paniscus)

Although biomarkers are often used for predicting morbidity and mortality in humans, similar data are lacking in our closest relatives. This study analyzed 16 biomarkers in zoo-housed chimpanzees and bonobos from serum samples collected during both routine and nonroutine veterinary immobilizations. Generalized linear and generalized linear mixed models were used to determine the efficacy of each biomarker to predict all-cause morbidity, defined as the presence of at least one chronic condition, or cardiac disease as a subset of all-cause morbidity. Cox proportional hazards models were used to examine associations between biomarkers and mortality risk from any cause. Analyses were conducted using two data sets for each species, one with all values retained (chimpanzees: n = 148; bonobos: n = 33) and the other from samples collected during routine immobilizations only (chimpanzees: n = 95; bonobos: n = 23). Consistent results across both data sets in chimpanzees included associations of higher cortisol with all-cause morbidity risk, lower creatinine with cardiac disease risk, and higher creatinine with mortality risk, and in bonobos were increased cardiac disease risk with higher cortisol and lower dehydroepiandrosterone-sulfate, fructosamine, and triglycerides. However, there were some inconsistencies between data sets, such as tumor necrosis factor-α predicting mortality risk positively in chimpanzees when all values were retained, but negatively for routine values only. Despite the close evolutionary relationships between chimpanzees and bonobos, the only result observed in both species was a negative association between albumin and mortality risk in the all values retained data sets. Thus, data suggest some biomarkers may be useful predictors of future health outcomes, although a better understanding of both individual and species variation in biomarkers and their contribution to health risks is needed.

Human papillomavirus vaccination and all-cause morbidity in adolescent girls: a cohort study of absence from school due to illness

Background

A growing body of evidence supports the safety of the human papillomavirus (HPV) vaccines. However, concerns about autonomic dysfunction syndromes and non-specific symptoms continue to linger. These conditions are not easily captured by traditional diagnostic classification schemes and call for innovative approaches to the study of vaccine safety which take more general measures of all-cause morbidity into account.

Methods

Taking advantage of the unique Danish registers, including regional registration of absence from school, we conducted a cohort study of 14 068 adolescent Danish girls attending 5th through 9th grade in public schools in the municipality of Copenhagen during 1 August 2013–23 January 2018. We obtained time-varying HPV vaccination status and demographic information from nationwide registers. Using Poisson regression with random effects, we estimated rate ratios (RRs) of absence due to illness, comparing HPV-vaccinated girls with unvaccinated girls with adjustment for grade, season, calendar period, demographic factors and random effects at the individual, class and school levels.

Results

Our study included 6 206 188 school days with 213 221 days of absence from school due to illness (absence rate, 3.4%). Comparing absence rates due to illness in HPV-vaccinated and unvaccinated girls yielded an adjusted RR of 1.00 (95% confidence interval [CI], 0.98–1.03).

Conclusions

Our study provides an important and novel contribution to HPV vaccine safety. Using absence from school records, we were able to address important safety concerns without relying on medical diagnoses. We conclude that HPV vaccination does not increase the risk of morbidity in any manner that manifests as absence from school due to illness.