Academic journal article Genetics

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

Academic journal article Genetics

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

Article excerpt

(ProQuest: ... denotes formulae omitted.)

INFECTIOUS disease constitutes a ubiquitous threat to plants, livestock, and human populations. Apart from its obvious impact on health and welfare of affected species and its associated production losses, infectious disease in plants and livestock also jeopardizes human food security and international trade. Despite substantial advances in disease diagnostics and medical interventions over recent years, the need for effective prevention strategies continues to exist.

There is increasing recognition that host genetics play an important role in the spread of infections within and between populations (Springbett et al. 2003; O'Brien and Nelson 2004; Lively 2010) and that genetic disease control strategies may offer a viable complement to epidemiological interventions. Compared to most epidemiological interventions, genetic control strategies are long-term, proactive (rather than reactive), and less likely to cause undesirable side effects such as environmental spillover or emergence of highly virulent or antimicrobial resistant pathogen strains (Gibson and Bishop 2005; Kemper et al. 2013). Their potential benefits are enhanced through the advent of high-throughput genomics, which in principle allows identification of individuals with high genetic risk purely based on their genetic material without ever needing to expose them to infectious pathogens. It is therefore not surprising that genetic improvement of disease resistance has become a prime target in livestock and plant genomics (Bishop and Woolliams 2014; Brooks-Pollock et al. 2015) and that prediction of genetic disease risk has become the focus of human genome projects (Chapman and Hill 2012). Nevertheless, theoretical evidence strongly indicates that existing genetic analyses tools, which focus almost exclusively on host resistance, capture only a fraction of the genetic variation inherent in epidemiological data (Bishop et al. 2012; Lipschutz-Powell et al. 2012a; Bishop and Woolliams 2014).

Epidemiological theory points to two key host traits affecting the spread of infectious diseases: host susceptibility, i.e., the propensity to become infected upon contact with infectious material, and host infectiousness, i.e., an individual's ability to transmit the infection (Lipschutz-Powell et al. 2014). The latter is composed of three traits under potential genetic control: contact rate, duration of infectious period, and infectivity, i.e., the ability to transmit infection per unit contact (Lloyd-Smith et al. 2006). Genetic-epidemiological models reveal that genetic heterogeneity in either trait can profoundly affect disease spread in populations (Nath et al. 2008; Doeschl-Wilson et al. 2011) and that a priori identification of highly susceptible or infectious individuals, e.g.,by their genetic makeup, would constitute powerful means to prevent future disease outbreaks (Lloyd-Smith et al. 2005; Matthews et al. 2006). Using epidemiological tracing data, Lloyd-Smith et al. (2005) established a link between recent large-scale outbreaks and the presence of superspreaders characterized by a small proportion of highly infectious individuals, thus providing evidence for phenotypic, although not genetic, variation in infectiousness.

To date it is not known to what extent superspreading is genetically determined as genetic parameters for infectiousness cannotbeaccuratelyestimatedwithexistingquantitativegenetic models (Lipschutz-Powell et al. 2012a,b, 2014). In particular, infectivity is a trait expressed through social interactions, as it affects the disease phenotype of group members rather than that of the host expressing it. If subject to heritable variation, infectivity can be defined as an indirect genetic effect (IGE), also known as an associative or a social genetic effect (Griffing 1967). Similarly, as susceptible individuals are more likely to become infected and thus also to transmit infection relative to resistant individuals that do not become infected in the first place, an individual's susceptibility can be considered as an IGE, as recently demonstrated by Anche et al. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.