To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Previous genetic association studies have failed to identify loci robustly associated with sepsis, and there have been no published genetic association studies or polygenic risk score analyses of patients with septic shock, despite evidence suggesting genetic factors may be involved. We systematically collected genotype and clinical outcome data in the context of a randomized controlled trial from patients with septic shock to enrich the presence of disease-associated genetic variants. We performed genomewide association studies of susceptibility and mortality in septic shock using 493 patients with septic shock and 2442 population controls, and polygenic risk score analysis to assess genetic overlap between septic shock risk/mortality with clinically relevant traits. One variant, rs9489328, located in AL589740.1 noncoding RNA, was significantly associated with septic shock (p = 1.05 × 10–10); however, it is likely a false-positive. We were unable to replicate variants previously reported to be associated (p < 1.00 × 10–6 in previous scans) with susceptibility to and mortality from sepsis. Polygenic risk scores for hematocrit and granulocyte count were negatively associated with 28-day mortality (p = 3.04 × 10–3; p = 2.29 × 10–3), and scores for C-reactive protein levels were positively associated with susceptibility to septic shock (p = 1.44 × 10–3). Results suggest that common variants of large effect do not influence septic shock susceptibility, mortality and resolution; however, genetic predispositions to clinically relevant traits are significantly associated with increased susceptibility and mortality in septic individuals.
The scarcity of Romano-British human remains from north-west England has hindered understanding of burial practice in this region. Here, we report on the excavation of human and non-human animal remains1 and material culture from Dog Hole Cave, Haverbrack. Foetal and neonatal infants had been interred alongside a horse burial and puppies, lambs, calves and piglets in the very latest Iron Age to early Romano-British period, while the mid- to late Roman period is characterised by burials of older individuals with copper-alloy jewellery and beads. This material culture is more characteristic of urban sites, while isotope analysis indicates that the later individuals were largely from the local area. We discuss these results in terms of burial ritual in Cumbria and rural acculturation. Supplementary material is available online (https://doi.org/10.1017/S0068113X20000136), and contains further information about the site and excavations, small finds, zooarchaeology, human osteology, site taphonomy, the palaeoenvironment, isotope methods and analysis, and finds listed in Benson and Bland 1963.
A range of decision-makers, including policy-makers, NGOs and local communities, have a stake in developing conservation interventions that are to be implemented on the ground. In order to ensure that decision-making is evidence-informed, the science community needs to engage these communities of policy and practice effectively. This chapter brings together work which explores how scientists can work effectively with decision-makers, using global case studies from South America, Australia, New Zealand and elsewhere to identify what works. It identifies 10 key tips for successful engagement : (1) know who you need to talk to, (2) engage early, (3) make it easy to engage, (4) include multiple knowledges, perspectives and worldviews, (5) think hard about power, (6) build trust, (7) good facilitation is key, (8) learn new engagement skills, (9) make use of existing spaces of collaboration, and (10) don't give up. While executing these tips will not guarantee successful engagement in every case, it will improve the chances for mutually beneficial relationships and hence better conservation outcomes.
The extended twin model is a unique design in the genetic epidemiology toolbox that allows to simultaneously estimate multiple causes of variation such as genetic and cultural transmission, genotype–environment covariance and assortative mating, among others. Nick Martin has played a key role in the conception of the model, the collection of substantially large data sets to test the model, the application of the model to a range of phenotypes, the publication of the results including cross-cultural comparisons, the evaluation of bias and power of the design and the further elaborations of the model, such as the children-of-twins design.
Dr Nick Martin has made enormous contributions to the field of behavior genetics over the past 50 years. Of his many seminal papers that have had a profound impact, we focus on his early work on the power of twin studies. He was among the first to recognize the importance of sample size calculation before conducting a study to ensure sufficient power to detect the effects of interest. The elegant approach he developed, based on the noncentral chi-squared distribution, has been adopted by subsequent researchers for other genetic study designs, and today remains a standard tool for power calculations in structural equation modeling and other areas of statistical analysis. The present brief article discusses the main aspects of his seminal paper, and how it led to subsequent developments, by him and others, as the field of behavior genetics evolved into the present era.
This short essay recounts the author’s interactions with Nick Martin in the years they both worked with Lindon Eaves at Virginia Commonwealth University. Although coming from very different academic traditions, they became close colleagues building their young careers together. Nick generously shared his statistical genetics expertise and the author taught Nick a thing or two about psychiatric illness.
The study and identification of genotype–environment interactions (GxE) has been a hot topic in the field of human genetics for several decades. Yet the extent to which GxE contributes to human behavior variability, and its mechanisms, remains largely unknown. Nick Martin has contributed important advances to the field of GxE for human behavior, which include methodological developments, novel analyses and reviews. Here, we will first review Nick’s contributions to the GxE research, which started during his PhD and consistently appears in many of his over 1000 publications. Then, we recount a project that led to an article testing the diathesis-stress model for the origins of depression. In this publication, we observed the presence of an interaction between polygenic risk scores for depression (the risk in our ‘genotype’) and stressful life events (the experiences from our ‘environment’), which provided the first empirical support of this model.
In the course of twin studies whose main focus was elucidation of genetic and environmental factors on behavioral traits, many twin researchers became aware of the strong tendency for dizygotic (DZ) twinning to run in families. Over four decades, Nick Martin and others initiated hormone and ultrasound studies, performed segregation and pedigree analyses, tested candidate genes, carried out linkage projects in sister pairs and formed large collaborations to illuminate the genetics of DZ twinning by genome-wide association studies and meta-analysis. This article summarizes the early work on hormone and genetic studies and describes the meta-analyses that have at last met with success in finding the first genes that predispose to DZ twinning, which also appear to influence many other female reproductive traits.
Nick Martin has had an outsized influence on the field of behavioral genetics. Much of this influence stems from his mentorship of young scientists. I describe Nick’s mentorship, and what makes it special, from a personal perspective.
This note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].
Genetic research into human sexuality was scarce at the end of last century. In 1992 Nick developed a 12-page questionnaire to send to twins to investigate the underpinnings of sexuality. The questionnaire included items about sexual orientation, sociosexuality and sexual behavior, and was completed by almost 5000 twins. The resulting data, unique at the time, has been used to investigate many previously unexaminable research questions. Here we describe how Nick’s questionnaire contributed to our understanding of human sexuality and how we got involved in this endeavor.
Twins, data and emails. Some of the words that first come to mind when I think of Nick. Lots of twins. With lots of data. And short single-finger-typed emails. And great wine. Well, it works, there is no doubt. That’s how I ended up in Australia, working on asthma genetics.
Blood cell concentrations for most cell types are highly heritable. Data from Nick Martin’s twin registry provided much of the data for the early heritability and linkage studies of blood cell related traits and have contributed significantly to more recent genomewide association studies that have successfully identified individual genetic loci.
Mapping genetic risk factors for endometriosis continues from early studies on women’s health initiated by Nick Martin and Susan Treloar. Their initial recruitment of endometriosis cases and family members received a major boost and became a flagship project within the Cooperative Research Centre (CRC) for the Discovery of Common Human Disease. We extended the study through a formal collaboration with Professor Stephen Kennedy and his group in Oxford. Our first joint scientific meeting was held in Brisbane and was sadly memorable as the day the planes were flown into the Twin Towers in New York. Our initial collaboration expanded into the International Endometriosis Genetics Consortium (IEGC). The IEGC now has 15 groups around the world, and the most recent meta-analysis will be published this year.
Nick Martin was a doctoral student of mine at the University of Birmingham in the mid 1970s. In this review, I discuss two of Nick’s earliest and most seminal contributions to the field of behavior genetics. First, Martin and Eaves’ (1977) extension of the model-fitting approach to multivariate data, which laid the theoretical groundwork for a generation of multivariate behavior genetic studies. Second, the Martin et al.’s (1978) manuscript on the power of the classical twin design, which showed that thousands of twin pairs would be required in order to reliably estimate components of variance, and has served as impetus for the formation of large-scale twin registries across the world. I discuss these contributions against the historical backdrop of a time when we and others were struggling with the challenge of figuring out how to incorporate gene-by-environment interaction, gene–environment correlation, mate selection and cultural transmission into more complex genetic models of human behavior.
Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick’s studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months — analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick’s research over the last 30 years and continues to do so.
This article describes Dr Nathan Gillespie’s PhD training and supervision under Professor Nick Martin and their ongoing collaborations. Drs Gillespie and Martin have collaborated on numerous biometrical genetic analyses applied to cross-sectional and longitudinal twin data, combined molecular and phenotypic modeling, as well as genomewide meta-analyses of psychoactive substance use and misuse. Dr Gillespie remains an active collaborator with Professor Martin, including ongoing data collection, analysis and publications related to the Brisbane Longitudinal Twin Study.