Neural and Molecular Mechanisms of Biological Embedding of Social Interactions

Childhood psychosocial adjustment and midlife obesity, diabetes and hypertension: prospective study from two birth cohorts

BACKGROUND

Understanding how childhood psychosocial adjustment (CPA) influences later life health outcomes is crucial for developing interventions to mitigate the long-term risk of cardiometabolic diseases (CMDs).

AIMS

To investigate the association between CPA and incident CMDs in mid-life, and the mediating roles of educational attainment, smoking habits and depression during young adulthood.

METHOD

A prospective cohort study utilised data from the 1958 National Child Development Study (NCDS; 1958-2013) and the 1970 British Cohort Study (BCS70; 1970-2018), encompassing 22 012 participants assessed for CPA in childhood, who were subsequently evaluated for educational attainment, smoking habits and depression in young adulthood, followed by assessments for CMDs in mid-life. CPA was assessed using the Bristol Social Adjustment Guides in the NCDS and the Rutter Child Behaviour Scale in the BCS70, with higher scores indicating poorer psychosocial adjustment. The primary outcomes were the mid-life incidences of hypertension, diabetes and obesity.

RESULTS

Compared with children in the lowest tertile for CPA scores, those in the middle tertile had an adjusted odds ratio for hypertension of 0.98 (95% CI 0.90-1.06), whereas those in the highest tertile had an odds ratio of 1.17 (95% CI 1.08-1.26). For diabetes, the corresponding odds ratios (95% CI) were 1.15 (0.98-1.35) and 1.39 (1.19-1.62). For obesity, the corresponding odds ratios (95% CI) were 1.08 (1.00-1.16) and 1.18 (1.09-1.27). These associations were partially mediated by educational attainment (2.4-13.9%) and depression during young adulthood (2.5-14.9%).

CONCLUSIONS

Poorer CPA is correlated with the development of hypertension, diabetes and obesity in mid-life. Interventions aimed at improving CPA may help in reducing the burden of these diseases in later life.

Integrating computer vision and molecular neurobiology to bridge the gap between behavior and the brain

The past decade of social insect research has seen rapid development in automated behavioral tracking and molecular profiling of the nervous system, two distinct but complementary lines of inquiry into phenotypic variation across individuals, colonies, populations, and species. These experimental strategies have developed largely in parallel, as automated tracking generates a continuous stream of behavioral data, while, in contrast, 'omics-based profiling provides a single 'snapshot' of the brain. Better integration of these approaches applied to studying variation in social behavior will reveal the underlying genetic and neurobiological mechanisms that shape the evolution and diversification of social life. In this review, we discuss relevant advances in both fields and propose new strategies to better elucidate the molecular and behavioral innovations that generate social life.

The evolution of decision-making mechanisms under competing demands

Animals in nature are constantly managing multiple demands, and decisions about how to adjust behavior in response to ecologically relevant demands is critical for fitness. Evidence for behavioral correlations across functional contexts (behavioral syndromes) and growing appreciation for shared proximate substrates of behavior prompts novel questions about the existence of distinct neural, molecular, and genetic mechanisms involved in decision-making. Those proximate mechanisms are likely to be an important target of selection, but little is known about how they evolve, their evolutionary history, or where they harbor genetic variation. Herein I provide a conceptual framework for understanding the evolution of mechanisms for decision-making, highlighting insights on decision-making in humans and model organisms, and sketch an emerging synthesis.

Transcriptomic responses to location learning by honeybee dancers are partly mirrored in the brains of dance-followers

The waggle dances of honeybees are a strikingly complex form of animal communication that underlie the collective foraging behaviour of colonies. The mechanisms by which bees assess the locations of forage sites that they have visited for representation on the dancefloor are now well-understood, but few studies have considered the remarkable backward translation of such information into flight vectors by dance-followers. Here, we explore whether the gene expression patterns that are induced through individual learning about foraging locations are mirrored when bees learn about those same locations from their nest-mates. We first confirmed that the mushroom bodies of honeybee dancers show a specific transcriptomic response to learning about distance, and then showed that approximately 5% of those genes were also differentially expressed by bees that follow dances for the same foraging sites, but had never visited them. A subset of these genes were also differentially expressed when we manipulated distance perception through an optic flow paradigm, and responses to learning about target direction were also in part mirrored in the brains of dance followers. Our findings show a molecular footprint of the transfer of learnt information from one animal to another through this extraordinary communication system, highlighting the dynamic role of the genome in mediating even very short-term behavioural changes.

Comparative genomics and the roots of human behavior

Advances in genomics provide tools to test whether similar behaviors in distinct species have statistically similar brain transcriptomic signatures. Here, we (a genomicist and a cognitive neuroscientist) suggest that these techniques can help cognitive scientists tackle some of the most pressing questions about the roots of human behavior.

Social complexity, life-history and lineage influence the molecular basis of castes in vespid wasps

A key mechanistic hypothesis for the evolution of division of labour in social insects is that a shared set of genes co-opted from a common solitary ancestral ground plan (a genetic toolkit for sociality) regulates caste differentiation across levels of social complexity. Using brain transcriptome data from nine species of vespid wasps, we test for overlap in differentially expressed caste genes and use machine learning models to predict castes using different gene sets. We find evidence of a shared genetic toolkit across species representing different levels of social complexity. We also find evidence of additional fine-scale differences in predictive gene sets, functional enrichment and rates of gene evolution that are related to level of social complexity, lineage and of colony founding. These results suggest that the concept of a shared genetic toolkit for sociality may be too simplistic to fully describe the process of the major transition to sociality.

Behavioral genetics and genomics: Mendel's peas, mice, and bees

The question of the heritability of behavior has been of long fascination to scientists and the broader public. It is now widely accepted that most behavioral variation has a genetic component, although the degree of genetic influence differs widely across behaviors. Starting with Mendel's remarkable discovery of "inheritance factors," it has become increasingly clear that specific genetic variants that influence behavior can be identified. This goal is not without its challenges: Unlike pea morphology, most natural behavioral variation has a complex genetic architecture. However, we can now apply powerful genome-wide approaches to connect variation in DNA to variation in behavior as well as analyses of behaviorally related variation in brain gene expression, which together have provided insights into both the genetic mechanisms underlying behavior and the dynamic relationship between genes and behavior, respectively, in a wide range of species and for a diversity of behaviors. Here, we focus on two systems to illustrate both of these approaches: the genetic basis of burrowing in deer mice and transcriptomic analyses of division of labor in honey bees. Finally, we discuss the troubled relationship between the field of behavioral genetics and eugenics, which reminds us that we must be cautious about how we discuss and contextualize the connections between genes and behavior, especially in humans.

Glyphosate impairs collective thermoregulation in bumblebees

Insects are facing a multitude of anthropogenic stressors, and the recent decline in their biodiversity is threatening ecosystems and economies across the globe. We investigated the impact of glyphosate, the most commonly used herbicide worldwide, on bumblebees. Bumblebee colonies maintain their brood at high temperatures via active thermogenesis, a prerequisite for colony growth and reproduction. Using a within-colony comparative approach to examine the effects of long-term glyphosate exposure on both individual and collective thermoregulation, we found that whereas effects are weak at the level of the individual, the collective ability to maintain the necessary high brood temperatures is decreased by more than 25% during periods of resource limitation. For pollinators in our heavily stressed ecosystems, glyphosate exposure carries hidden costs that have so far been largely overlooked.

Context-dependent influence of threat on honey bee social network dynamics and brain gene expression

Adverse social experience affects social structure by modifying the behavior of individuals, but the relationship between an individual's behavioral state and its response to adversity is poorly understood. We leveraged naturally occurring division of labor in honey bees and studied the biological embedding of environmental threat using laboratory assays and automated behavioral tracking of whole colonies. Guard bees showed low intrinsic levels of sociability compared with foragers and nurse bees, but large increases in sociability following exposure to a threat. Threat experience also modified the expression of caregiving-related genes in a brain region called the mushroom bodies. These results demonstrate that the biological embedding of environmental experience depends on an individual's societal role and, in turn, affects its future sociability.

Epigenetic MRI: Noninvasive imaging of DNA methylation in the brain

Dynamic epigenetic activity is a fundamental mechanism underpinning how the brain changes its function during development and aging and in response to environmental and disease stimuli. We developed a technology called epigenetic MRI (eMRI) that enables noninvasive imaging of DNA methylation in the brain, a major epigenetic mechanism. eMRI reveals strong regional differences in global DNA methylation in pig brains, a model with stronger resemblance to human brains than are rodents. Given the noninvasive nature of eMRI, our results pave the way for a DNA-methylation imaging paradigm for living human brains. We expect eMRI to enable many studies to unravel the molecular control of brain function and disease.

Both neuronal and genetic mechanisms regulate brain function. While there are excellent methods to study neuronal activity in vivo, there are no nondestructive methods to measure global gene expression in living brains. Here, we present a method, epigenetic MRI (eMRI), that overcomes this limitation via direct imaging of DNA methylation, a major gene-expression regulator. eMRI exploits the methionine metabolic pathways for DNA methylation to label genomic DNA through ¹³C-enriched diets. A ¹³C magnetic resonance spectroscopic imaging method then maps the spatial distribution of labeled DNA. We validated eMRI using pigs, whose brains have stronger similarity to humans in volume and anatomy than rodents, and confirmed efficient ¹³C-labeling of brain DNA. We also discovered strong regional differences in global DNA methylation. Just as functional MRI measurements of regional neuronal activity have had a transformational effect on neuroscience, we expect that the eMRI signal, both as a measure of regional epigenetic activity and as a possible surrogate for regional gene expression, will enable many new investigations of human brain function, behavior, and disease.

Back to the basics? Transcriptomics offers integrative insights into the role of space, time and the environment for gene expression and behaviour

Fuelled by the ongoing genomic revolution, broadscale RNA expression surveys are fast replacing studies targeting one or a few genes to understand the molecular basis of behaviour. Yet, the timescale of RNA-sequencing experiments and the dynamics of neural gene activation are insufficient to drive real-time switches between behavioural states. Moreover, the spatial, functional and transcriptional complexity of the brain (the most commonly targeted tissue in studies of behaviour) further complicates inference. We argue that a Central Dogma-like 'back-to-basics' assumption that gene expression changes cause behaviour leaves some of the most important aspects of gene-behaviour relationships unexplored, including the roles of environmental influences, timing and feedback from behaviour-and the environmental shifts it causes-to neural gene expression. No perfect experimental solutions exist but we advocate that explicit consideration, exploration and discussion of these factors will pave the way toward a richer understanding of the complicated relationships between genes, environments, brain gene expression and behaviour over developmental and evolutionary timescales.