Using non-invasive behavioral and physiological data to measure biological age in wild baboons.

Biological aging is near-ubiquitous in the animal kingdom, but its timing and pace vary between individuals and over lifespans. Prospective, individual-based studies of wild animals-especially non-human primates-help identify the social and environmental drivers of this variation by indicating the conditions and exposure windows that affect aging processes. However, measuring individual biological age in wild primates is challenging because several of the most promising methods require invasive sampling. Here, we leverage observational data on behavior and physiology, collected non-invasively from 319 wild female baboons across 2402 female-years of study, to develop a composite predictor of age: the non-invasive physiology and behavior (NPB) clock. We found that age predictions from the NPB clock explained 51% of the variation in females' known ages. Further, deviations from the clock's age predictions predicted female survival: females predicted to be older than their known ages had higher adult mortality. Finally, females who experienced harsh early-life conditions were predicted to be about 6 months older than those who grew up in more benign conditions. While the relationship between early adversity and NPB age is noisy, this estimate translates to a predicted 2-3 year reduction in mean adult lifespan in our model. A constraint of our clock is that it is tailored to data collection approaches implemented in our study population. However, many of the clock's components have analogs in other populations, suggesting that non-invasive data can provide broadly applicable insight into heterogeneity in biological age in natural populations.

Synchrony and idiosyncrasy in the gut microbiome of wild baboons.

Human gut microbial dynamics are highly individualized, making it challenging to link microbiota to health and to design universal microbiome therapies. This individuality is typically attributed to variation in host genetics, diets, environments and medications but it could also emerge from fundamental ecological forces that shape microbiota more generally. Here, we leverage extensive gut microbial time series from wild baboons-hosts who experience little interindividual dietary and environmental heterogeneity-to test whether gut microbial dynamics are synchronized across hosts or largely idiosyncratic. Despite their shared lifestyles, baboon microbiota were only weakly synchronized. The strongest synchrony occurred among baboons living in the same social group, probably because group members range over the same habitat and simultaneously encounter the same sources of food and water. However, this synchrony was modest compared to each host's personalized dynamics. In support, host-specific factors, especially host identity, explained, on average, more than three times the deviance in longitudinal dynamics compared to factors shared with social group members and ten times the deviance of factors shared across the host population. These results contribute to mounting evidence that highly idiosyncratic gut microbiomes are not an artefact of modern human environments and that synchronizing forces in the gut microbiome (for example, shared environments, diets and microbial dispersal) are not strong enough to overwhelm key drivers of microbiome personalization, such as host genetics, priority effects, horizontal gene transfer and functional redundancy.

Gut microbiome heritability is nearly universal but environmentally contingent.

Relatives have more similar gut microbiomes than nonrelatives, but the degree to which this similarity results from shared genotypes versus shared environments has been controversial. Here, we leveraged 16,234 gut microbiome profiles, collected over 14 years from 585 wild baboons, to reveal that host genetic effects on the gut microbiome are nearly universal. Controlling for diet, age, and socioecological variation, 97% of microbiome phenotypes were significantly heritable, including several reported as heritable in humans. Heritability was typically low (mean = 0.068) but was systematically greater in the dry season, with low diet diversity, and in older hosts. We show that longitudinal profiles and large sample sizes are crucial to quantifying microbiome heritability, and indicate scope for selection on microbiome characteristics as a host phenotype.