A standardized instrument quantifying risk factors associated with bi-directional transmission of SARS-CoV-2 and other zoonotic pathogens: The COVID-19 Human-Animal Interactions Survey (CHAIS)

SARS-CoV-2 (CoV-2), which surfaced in late 2019 in Wuhan City, China, most likely originated in bats and rapidly spread among humans globally, harming and disrupting livelihoods worldwide. Early into the pandemic, reports of CoV-2 diagnoses in pets and other animals emerged, including dogs, cats, farmed mink, and some large felids (tigers and lions) from various countries. While most CoV-2 positive animals were confirmed to have been in close contact with CoV-2 positive humans, there has been a paucity of published evidence to-date describing risk factors associated with CoV-2 transmission among humans and domestic and wild animals. The COVID-19 Human-Animal Interactions Survey (CHAIS) was developed through a cross-CEIRS Center collaboration to provide a standardized survey describing human-animal interaction during the pandemic and to evaluate behavioral, spatiotemporal, and biological risk factors associated with bi-directional zoonotic transmission of CoV-2 within households and other shared environments. CHAIS measures four broad domains of transmission risk; 1) intensity and risk of infection among human hosts, 2) spatial characteristics of shared environments, 3) behaviors and human-animal interactions, and 4) animal susceptibility to infection and propensity for onward spread. Following the development of CHAIS, with a One Health approach, a multidisciplinary group of experts (n=20) was invited to review and provide feedback on the survey for content validity. Expert feedback was incorporated into two final survey formats- a long-form and an abridged version for which specific core questions addressing zoonotic and reverse zoonotic transmission were identified. Both forms are modularized, with each section having the capacity to serve as independent instruments, allowing researchers to customize the survey based on context and research-specific needs. Further adaptations for studies seeking to investigate other zoonotic pathogens with similar routes of transmission (i.e. respiratory, direct contact) are also possible. The CHAIS instrument is a standardized human-animal interaction survey developed to provide important data on risk factors that guide transmission of CoV-2 from humans to animals, with great utility in capturing information of zoonotic transmission risk factors for CoV-2 and other similar pathogens.

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.

First-year college students’ weight change is influenced by their randomly assigned roommates’ BMI

Background There is ongoing debate about whether friends’ greater similarity in Body Mass Index (BMI) than non-friends is due to friend selection, shared environments, or peer influence. Methods First-year college students (n = 104) from a southwestern U.S. university were randomly assigned roommates during the university’s housing process, effectively removing friend selection effects. Participant BMI was measured up to four times (T1-T4) across 2015–2016. The influence of roommate baseline BMI (T1) on change in participant BMI over time (T2-T4) was analyzed using a linear mixed effects model adjusted for individual socio-demographics, linear time trends, baseline BMI, and physical clustering of students. A sensitivity analysis examining floormates was also conducted. Results Consistent with roommate influence, participants randomized to roommates with a higher BMI gained more weight between times T2 and T4 (β = 0.06; 95% CI = 0.02, 0.10). No shared environment effects (shared campus or floor) were found. Conclusions Randomly assigned roommates influenced each other's weight trajectories. This clarifies that BMI convergence can occur outside of friend selection or shared environments mechanisms.

Twin studies with unmet assumptions are biased towards genetic heritability

SummaryFor a century [1,2], studies of monozygotic and dizygotic twins have yielded estimates of trait heritability. The clever logic behind them is that while both types of twins share environments, their genetic overlap is different. Hence, larger trait correlations between monozygotic compared to dizygotic twins indicate heritability (nature), whereas similar correlations indicate shared environmental influences (nurture), and low correlations indicate shaping through non-shared environments (external influences and measurement error). While many have written on the assumptions that both types of twins share equal environments [3–5], and that parental genetics and environment are independent [6,7]; fewer have put their data where their mouth is. Here, the impacts of unmet assumptions were investigated using a generative mixture model of twin phenotypes. The results indicated that violations of the equal environments assumption yielded large overestimations of heritability and underestimations of shared environmental influences. On the other hand, when parental genetics shaped twins’ shared environments, only minor non-linear biases against heritability emerged. Finally, realistic levels of measurement error uniformly depressed estimates for genetic and shared environmental factors. In sum, twin studies are particularly susceptible to overestimation of genetic and non-shared environmental influences. This bias could explain why some traits, such as attitudes towards property taxes [8], show suspiciously high heritability without a biologically plausible mechanism. Particularly in the context of traits with convincing mechanisms of cultural transmission [9–11] and complex gene-environment interactions [6], researchers should not allow biases in twin studies to overestimate heritability.

4. What are the contributions of environments and genes to intelligence differences?

‘What are the contributions of environments and genes to intelligence differences?’ asks whether genetic inheritance and the environments people experience affect intelligence differences. Researchers use two main resources to answer this question: twins and samples of DNA. Studies of identical and non-identical twins are used to show the contributions of genes, shared environment, and non-shared environment to people’s differences in traits. Twin studies tell us that by adulthood, about two-thirds of intelligence differences are caused by how people vary in their genetic inheritance, and that both shared and non-shared environments make significant contributions to intelligence differences. The introduction of genome-wide association studies in 2011 has provided a new method of estimating the heritability of intelligence.

Parent–Child Value Similarity

Parent–child value similarity is often considered a hallmark of successful intergenerational socialization. Traditional approaches to the study of relationships among generations view value socialization as a top-down phenomenon in which parents transmit their values to their children in a unidirectional and often deterministic manner. Instead, in this chapter, the authors argue for considering parent–child value similarity as the result of a complex network of mutual influences among parents, children, and their shared environments. In particular, we propose a framework that considers four interdependent pathways to parent–child value similarity: parental influence, child influence, genetic effects, and overlap among the environmental antecedents of values. For each of these pathways, as well as for their interactions and correlations, the authors provide and discuss some examples for a better understanding of the shared value development.