The Hawaiian archipelago was formerly home to one of the most species-rich land snail faunas (> 752 species), with levels of endemism > 99%. Many native Hawaiian land snail species are now extinct, and the remaining fauna is vulnerable. Unfortunately, lack of information on critical habitat requirements for Hawaiian land snails limits the development of effective conservation strategies. The purpose of this study was to examine the plant host preferences of native arboreal land snails in Puʻu Kukui Watershed, West Maui, Hawaiʻi, and compare these patterns to those from similar studies on the islands of Oʻahu and Hawaiʻi. Concordant with studies on other islands, we found that four species from three diverse families of snails in Puʻu Kukui Watershed had preferences for a few species of understorey plants. These were not the most abundant canopy or mid canopy species, indicating that forests without key understorey plants may not support the few remaining lineages of native snails. Preference for Broussaisia arguta among various island endemic snails across all studies indicates that this species is important for restoration to improve snail habitat. As studies examining host plant preferences are often incongruent with studies examining snail feeding, we suggest that we are in the infancy of defining what constitutes critical habitat for most Hawaiian arboreal snails. However, our results indicate that preserving diverse native plant assemblages, particularly understorey plant species, which facilitate key interactions, is critical to the goal of conserving the remaining threatened snail fauna.

Recent studies have used Mendelian randomization (MR) to investigate the observational association between low birth weight (BW) and increased risk of cardiometabolic outcomes, specifically cardiovascular disease, glycemic traits, and type 2 diabetes (T2D), and inform on the validity of the Barker hypothesis. We used simulations to assess the validity of these previous MR studies, and to determine whether a better formulated model can be used in this context. Genetic and phenotypic data were simulated under a model of no direct causal effect of offspring BW on cardiometabolic outcomes and no effect of maternal genotype on offspring cardiometabolic risk through intrauterine mechanisms; where the observational relationship between BW and cardiometabolic risk was driven entirely by horizontal genetic pleiotropy in the offspring (i.e. offspring genetic variants affecting both BW and cardiometabolic disease simultaneously rather than a mechanism consistent with the Barker hypothesis). We investigated the performance of four commonly used MR analysis methods (weighted allele score MR (WAS-MR), inverse variance weighted MR (IVW-MR), weighted median MR (WM-MR), and MR-Egger) and a new approach, which tests the association between maternal genotypes related to offspring BW and offspring cardiometabolic risk after conditioning on offspring genotype at the same loci. We caution against using traditional MR analyses, which do not take into account the relationship between maternal and offspring genotypes, to assess the validity of the Barker hypothesis, as results are biased in favor of a causal relationship. In contrast, we recommend the aforementioned conditional analysis framework utilizing maternal and offspring genotypes as a valid test of not only the Barker hypothesis, but also to investigate hypotheses relating to the Developmental Origins of Health and Disease more broadly.

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.

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.

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.

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.

The classical twin design relies on a number of strong number of assumptions in order to yield unbiased estimates of heritability. This includes the equal environments assumption — that monozygotic and dizygotic twins experience similar degrees of environmental similarity — an assumption that is likely to be violated in practice for many traits of interest. An alternative method of estimating heritability that does not suffer from many of these limitations is to model trait similarity between sibling pairs as a function of their empirical genome-wide identity by descent sharing, estimated from genetic markers. In this review, I recount the story behind Nick Martin’s and my development of this method, our first attempts at applying it in a human population and more recent studies using the original and related methods to estimate trait heritability.

Despite decades of suicide research, our ability to predict suicide has not changed. Why is this the case? We outline the unique challenges facing suicide research. Borrowing successful strategies from other medical fields, we propose specific research directions that aim to translate scientific findings into meaningful clinical impact.

Drawing on a landscape analysis of existing data-sharing initiatives, in-depth interviews with expert stakeholders, and public deliberations with community advisory panels across the U.S., we describe features of the evolving medical information commons (MIC). We identify participant-centricity and trustworthiness as the most important features of an MIC and discuss the implications for those seeking to create a sustainable, useful, and widely available collection of linked resources for research and other purposes.

Important Bird and Biodiversity Areas (IBAs) are sites identified as being globally important for the conservation of bird populations on the basis of an internationally agreed set of criteria. We present the first review of the development and spread of the IBA concept since it was launched by BirdLife International (then ICBP) in 1979 and examine some of the characteristics of the resulting inventory. Over 13,000 global and regional IBAs have so far been identified and documented in terrestrial, freshwater and marine ecosystems in almost all of the world’s countries and territories, making this the largest global network of sites of significance for biodiversity. IBAs have been identified using standardised, data-driven criteria that have been developed and applied at global and regional levels. These criteria capture multiple dimensions of a site’s significance for avian biodiversity and relate to populations of globally threatened species (68.6% of the 10,746 IBAs that meet global criteria), restricted-range species (25.4%), biome-restricted species (27.5%) and congregatory species (50.3%); many global IBAs (52.7%) trigger two or more of these criteria. IBAs range in size from < 1 km2 to over 300,000 km2 and have an approximately log-normal size distribution (median = 125.0 km2, mean = 1,202.6 km2). They cover approximately 6.7% of the terrestrial, 1.6% of the marine and 3.1% of the total surface area of the Earth. The launch in 2016 of the KBA Global Standard, which aims to identify, document and conserve sites that contribute to the global persistence of wider biodiversity, and whose criteria for site identification build on those developed for IBAs, is a logical evolution of the IBA concept. The role of IBAs in conservation planning, policy and practice is reviewed elsewhere. Future technical priorities for the IBA initiative include completion of the global inventory, particularly in the marine environment, keeping the dataset up to date, and improving the systematic monitoring of these sites.