Advancing tools to promote health equity across European Union regions : The EURO-HEALTHY project

Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement. Under the EURO-HEALTHY project, tools combining the technical elements of multi-criteria value models and the social elements of participatory processes were developed to measure health in multiple dimensions and to inform policies. The flagship tool is the Population Health Index (PHI), a multidimensional measure that evaluates health from the lens of equity in health determinants and health outcomes, further divided into sub-indices. Foresight tools for policy analysis were also developed, namely: (1) scenarios of future patterns of population health in Europe in 2030, combining group elicitation with the Extreme-World method and (2) a multi-criteria evaluation framework informing policy appraisal (case study of Lisbon). Finally, a WebGIS was built to map and communicate the results to wider audiences. The Population Health Index was applied to all European Union (EU) regions, indicating which regions are lagging behind and where investments are most needed to close the health gap. Three scenarios for 2030 were produced - (1) the 'Failing Europe' scenario (worst case/increasing inequalities), (2) the 'Sustainable Prosperity' scenario (best case/decreasing inequalities) and (3) the 'Being Stuck' scenario (the EU and Member States maintain the status quo). Finally, the policy appraisal exercise conducted in Lisbon illustrates which policies have higher potential to improve health and how their feasibility can change according to different scenarios. The article makes a theoretical and practical contribution to the field of population health. Theoretically, it contributes to the conceptualisation of health in a broader sense by advancing a model able to integrate multiple aspects of health, including health outcomes and multisectoral determinants. Empirically, the model and tools are closely tied to what is measurable when using the EU context but offering opportunities to be upscaled to other settings

Target Region Selection Is a Critical Determinant of Community Fingerprints Generated by 16S Pyrosequencing

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1–V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacer and Enterococcus predominated in the community generated by V4–V6 primers, and the most numerous genera in the V7–V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4–V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7–V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1–V3 and V7–V9 primers providesd results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities

Microbial Co-occurrence Relationships in the Human Microbiome

The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and Streptococcus in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and Bacteroides in the gut) often compete, while potential pathogens (e.g. Treponema and Prevotella in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome.National Institutes of Health (U.S.) (grant CA139193)Fonds Wetenschappelijk Onderzoek – VlaanderenJuvenile Diabetes Research Foundation InternationalNational Institutes of Health (U.S.) (grant NIH U54HG004969)Crohn's and Colitis Foundation of AmericaNational Science Foundation (U.S.) (NSF DBI-1053486)United States. Army Research Office (ARO W911NF-11-1-0473)National Institutes of Health (U.S.) (grant NIH 1R01HG005969

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Citation: Chapman, J. A., Mascher, M., Buluç, A., Barry, K., Georganas, E., Session, A., . . . Rokhsar, D. S. (2015). A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome. Genome Biology, 16(1). doi:10.1186/s13059-015-0582-8Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population. © 2015 Chapman et al. licensee BioMed Central.Additional Authors: Muehlbauer, G. J.;Stein, N.;Rokhsar, D. S

Pollinator-flower interactions in gardens during the COVID-19 pandemic lockdown of 2020

During the main COVID-19 global pandemic lockdown period of 2020 an impromptu set of pollination ecologists came together via social media and personal contacts to carry out standardised surveys of the flower visits and plants in gardens. The surveys involved 67 rural, suburban and urban gardens, of various sizes, ranging from 61.18° North in Norway to 37.96° South in Australia, resulting in a data set of 25,174 rows, with each row being a unique interaction record for that date/site/plant species, and comprising almost 47,000 visits to flowers, as well as records of flowers that were not visited by pollinators, for over 1,000 species and varieties belonging to more than 460genera and 96plant families. The more than 650 species of flower visitors belong to 12 orders of invertebrates and four of vertebrates. In this first publication from the project, we present a brief description of the data and make it freely available for any researchers to use in the future, the only restriction being that they cite this paper in the first instance. The data generated from these global surveys will provide scientific evidence to help us understand the role that private gardens (in urban, rural and suburban areas) can play in conserving insect pollinators and identify management actions to enhance their potential

Demographic, clinical, and service-use characteristics related to the clinician’s recommendation to transition from child to adult mental health services

Purpose: The service configuration with distinct child and adolescent mental health services (CAMHS) and adult mental health services (AMHS) may be a barrier to continuity of care. Because of a lack of transition policy, CAMHS clinicians have to decide whether and when a young person should transition to AMHS. This study describes which characteristics are associated with the clinicians’ advice to continue treatment at AMHS. Methods: Demographic, family, clinical, treatment, and service-use characteristics of the MILESTONE cohort of 763 young people from 39 CAMHS in Europe were assessed using multi-informant and standardized assessment tools. Logistic mixed models were fitted to assess the relationship between these characteristics and clinicians’ transition recommendations. Results: Young people with higher clinician-rated severity of psychopathology scores, with self- and parent-reported need for ongoing treatment, with lower everyday functional skills and without self-reported psychotic experiences were more likely to be recommended to continue treatment. Among those who had been recommended to continue treatment, young people who used psychotropic medication, who had been in CAMHS for more than a year, and for whom appropriate AMHS were available were more likely to be recommended to continue treatment at AMHS. Young people whose parents indicated a need for ongoing treatment were more likely to be recommended to stay in CAMHS. Conclusion: Although the decision regarding continuity of treatment was mostly determined by a small set of clinical characteristics, the recommendation to continue treatment at AMHS was mostly affected by service-use related characteristics, such as the availability of appropriate services