Socio-economic and food system drivers of nutrition and health transitions in The Gambia from 1990 to 2017 - Zakari Ali; Pauline F.D. Scheelbeek; Sarah Dalzell; Genevieve Hadida; Alcade C. Segnon; Sulayman M'boob; Andrew M. Prentice; Rosemary Green (Global Food Security, 2023)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities - Andrew Siefert; Cyrille Violle; Loïc Chalmandrier; Cécile H. Albert; Adrien Taudiere; Alex Fajardo; Lonnie W. Aarssen; Christopher Baraloto; Marcos B. Carlucci; Marcus V. Cianciaruso; Vinícius de L. Dantas; Francesco de Bello; et al. (Ecology Letters, 2015)
Recent studies have shown that accounting for intraspecific trait variation ( ITV ) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta‐analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole‐plant (e.g. plant height) vs. organ‐level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait‐based community and ecosystem studies.

HLA class I, KIR, and genome-wide SNP diversity in the RV144 Thai phase 3 HIV vaccine clinical trial - Heather A. Prentice; Philip K. Ehrenberg; Karen M. Baldwin; Aviva Geretz; Charla Andrews; Sorachai Nitayaphan; Supachai Rerks-Ngarm; Jaranit Kaewkungwal; Punnee Pitisuttithum; Robert J. O’Connell; Merlin L. Robb; Jerome H. Kim; et al. (Immunogenetics, 2014)

Meta-analysis of new genome-wide association studies of colorectal cancer risk - Ulrike Peters; Carolyn M. Hutter; Li Hsu; Fredrick R. Schumacher; David V. Conti; Christopher S. Carlson; Christopher K. Edlund; Robert W. Haile; Steven Gallinger; Brent W. Zanke; Mathieu Lemire; Jagadish Rangrej; et al. (Human Genetics, 2012)

Common polymorphic variation in the genetically diverse African insulin gene and its association with size at birth - Clive J. Petry; Pura Rayco-Solon; Anthony J. C. Fulford; John D. H. Stead; Dianne L. Wingate; Ken K. Ong; Giorgio Sirugo; Andrew M. Prentice; David B. Dunger (Human Genetics, 2009)

Global response of terrestrial ecosystem structure and function to CO 2 and climate change: results from six dynamic global vegetation models - Wolfgang Cramer; Alberte Bondeau; F. Ian Woodward; I. Colin Prentice; Richard A. Betts; Victor Brovkin; Peter M. Cox; Veronica Fisher; Jonathan A. Foley; Andrew D. Friend; Chris Kucharik; Mark R. Lomas; et al. (Global Change Biology, 2001)
Summary The possible responses of ecosystem processes to rising atmospheric CO 2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO 2 ( Wigley et al . 1991 ), and by climate changes resulting from effective CO 2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2‐SUL. Simulations with changing CO 2 alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y −1 during the 1990s, rising to 3.7–8.6 Pg C y −1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y −1 ) and a century later (0.3–6.6 Pg C y −1 ) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO 2 effects at high CO 2 concentrations. Four out of the six models show a further, climate‐induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO 2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO 2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO 2 and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO 2 and climate change.