Assortative mating at loci under recent natural selection in humans

Characterizing super-spreaders using population-level weighted social networks in rural communities

Sociocentric network maps of entire populations, when combined with data on the nature of constituent dyadic relationships, offer the dual promise of advancing understanding of the relevance of networks for disease transmission and of improving epidemic forecasts. Here, using detailed sociocentric data collected over 4 years in a population of 24 702 people in 176 villages in Honduras, along with diarrhoeal and respiratory disease prevalence, we create a social-network-powered transmission model and identify super-spreading nodes as well as the nodes most vulnerable to infection, using agent-based Monte Carlo network simulations. We predict the extent of outbreaks for communicable diseases based on detailed social interaction patterns. Evidence from three waves of population-level surveys of diarrhoeal and respiratory illness indicates a meaningful positive correlation with the computed super-spreading capability and relative vulnerability of individual nodes. Previous research has identified super-spreaders through retrospective contact tracing or simulated networks. By contrast, our simulations predict that a node's super-spreading capability and its vulnerability in real communities are significantly affected by their connections, the nature of the interaction across these connections, individual characteristics (e.g. age and sex) that affect a person's ability to disperse a pathogen, and also the intrinsic characteristics of the pathogen (e.g. infectious period and latency). This article is part of the theme issue 'Data science approach to infectious disease surveillance'.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

COVID-19 Pandemic on Fire: Evolved Propensities for Nocturnal Activities as a Liability Against Epidemiological Control

Humans have been using fire for hundreds of millennia, creating an ancestral expansion toward the nocturnal niche. The new adaptive challenges faced at night were recurrent enough to amplify existing psychological variation in our species. Night-time is dangerous and mysterious, so it selects for individuals with higher tendencies for paranoia, risk-taking, and sociability (because of security in numbers). During night-time, individuals are generally tired and show decreased self-control and increased impulsive behaviors. The lower visibility during night-time favors the partial concealment of identity and opens more opportunities for disinhibition of self-interested behaviors. Indeed, individuals with an evening-oriented chronotype are more paranoid, risk-taking, extraverted, impulsive, promiscuous, and have higher antisocial personality traits. However, under some circumstances, such as respiratory pandemics, the psychobehavioral traits favored by the nocturnal niche might be counter-productive, increasing contagion rates of a disease that can evade the behavioral immune system because its disease cues are often nonexistent or mild. The eveningness epidemiological liability hypothesis presented here suggests that during the COVID-19 pandemic, the evening-oriented psychobehavioral profile can have collectively harmful consequences: there is a clash of core tendencies between the nocturnal chronotype and the recent viral transmission-mitigating safety guidelines and rules. The pandemic safety protocols disrupt much normal social activity, particularly at night when making new social contacts is desired. The SARS-CoV-2 virus is contagious even in presymptomatic and asymptomatic individuals, which enables it to mostly evade our evolved contagious disease avoidance mechanisms. A growing body of research has indirectly shown that individual traits interfering with social distancing and anti-contagion measures are related to those of the nocturnal chronotype. Indeed, some of the social contexts that have been identified as superspreading events occur at night, such as in restaurants, bars, and nightclubs. Furthermore, nocturnal environmental conditions favor the survival of the SARS-CoV-2 virus much longer than daytime conditions. We compare the eveningness epidemiological liability hypothesis with other factors related to non-compliance with pandemic safety protocols, namely sex, age, and life history. Although there is not yet a direct link between the nocturnal chronotype and non-compliance with pandemic safety protocols, security measures and future empirical research should take this crucial evolutionary mismatch and adaptive metaproblem into account, and focus on how to avoid nocturnal individuals becoming superspreaders, offering secure alternatives for nocturnal social activities.