T wave abnormalities, high body mass index, current smoking and high lipoprotein (a) levels predict the development of major abnormal Q/QS patterns 20 years later. A population-based study

BACKGROUND: Most studies on risk factors for development of coronary heart disease (CHD) have been based on the clinical outcome of CHD. Our aim was to identify factors that could predict the development of ECG markers of CHD, such as abnormal Q/QS patterns, ST segment depression and T wave abnormalities, in 70-year-old men, irrespective of clinical outcome. METHODS: Predictors for development of different ECG abnormalities were identified in a population-based study using stepwise logistic regression. Anthropometrical and metabolic factors, ECG abnormalities and vital signs from a health survey of men at age 50 were related to ECG abnormalities identified in the same cohort 20 years later. RESULTS: At the age of 70, 9% had developed a major abnormal Q/QS pattern, but 63% of these subjects had not been previously hospitalized due to MI, while 57% with symptomatic MI between age 50 and 70 had no major Q/QS pattern at age 70. T wave abnormalities (Odds ratio 3.11, 95% CI 1.18–8.17), high lipoprotein (a) levels, high body mass index (BMI) and smoking were identified as significant independent predictors for the development of abnormal major Q/QS patterns. T wave abnormalities and high fasting glucose levels were significant independent predictors for the development of ST segment depression without abnormal Q/QS pattern. CONCLUSION: T wave abnormalities on resting ECG should be given special attention and correlated with clinical information. Risk factors for major Q/QS patterns need not be the same as traditional risk factors for clinically recognized CHD. High lipoprotein (a) levels may be a stronger risk factor for silent myocardial infarction (MI) compared to clinically recognized MI

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Interrogating violence against women and state violence policy: Gendered intersectionalities and the quality of policy in The Netherlands, Sweden and the Uk

This article builds on feminist scholarship on intersectionality to address violence against women, and state policy thereon. It takes up the challenge of analysing the complex, situated and spatial relationship between theorizing on violence against women and state policy on such violence. Drawing on extensive comparative European data, it explores the relations of gender and intersectionality, conceptualized as gendered intersectionalities, by examining how multiple inequalities are made visible and invisible in state policy and debates in the Netherlands, Sweden and the UK. Attention is paid to different forms of gendered intersectionalities in policy, for example, tendencies to degender violence against women. A key aim of the article is to investigate how comparative analysis can be a starting point for assessing if, how and to what extent the inclusion of multiple inequalities could increase the quality of policy, for both reducing and stopping violence, and assisting those subject to violence

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Body mass index vs deuterium dilution method for establishing childhood obesity prevalence, Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania

Objective -- To compare the World Health Organization (WHO) body mass index (BMI)-for-age definition of obesity against measured body fatness in African children. Methods -- In a prospective multicentre study over 2013 to 2017, we recruited 1516 participants aged 8 to 11 years old from urban areas of eight countries (Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania). We measured height and weight and calculated BMI-for-age using WHO standards. We measured body fatness using the deuterium dilution method and defined excessive body fat percentage as > 25% in boys and > 30% in girls. We calculated the sensitivity and specificity of BMI z-score > +2.00 standard deviations (SD) and used receiver operating characteristic analysis and the Youden index to determine the optimal BMI z-score cut-off for classifying excessive fatness. Findings -- The prevalence of excessive fatness was over three times higher than BMI-for-age-defined obesity: 29.1% (95% CI: 26.8 to 31.4; 441 children) versus 8.8% (95% CI: 7.5 to 10.4; 134 children). The sensitivity of BMI z-score > +2.00 SD was low (29.7%, 95% CI: 25.5 to 34.2) and specificity was high (99.7%, 95% CI: 99.2 to 99.9). The receiver operating characteristic analysis found that a BMI z-score +0.58 SD would optimize sensitivity, and at this cut-off the area under the curve was 0.86, sensitivity 71.9% (95% CI: 67.4 to 76.0) and specificity 91.1% (95% CI: 89.2 to 92.7). Conclusion -- While BMI remains a practical tool for obesity surveillance, it underestimates excessive fatness and this should be considered when planning future African responses to the childhood obesity pandemic

Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

ACKNOWLEDGEMENTS This study was supported by the project “C and N models inter-comparison and improvement to assess management options for GHG mitigation in agro-systems worldwide” (CN-MIP, 2014- 2017), which received funding by a multi-partner call on agricultural greenhouse gas research of the Joint Programming Initiative ‘FACCE’ through national financing bodies. S. Recous, R. Farina, L. Brilli, G. Bellocchi and L. Bechini received mobility funding by way of the French Italian GALILEO programme (CLIMSOC project). The authors acknowledge particularly the data holders for the Long Term Bare-Fallows, who made their data available and provided additional information on the sites: V. Romanenkov, B.T. Christensen, T. Kätterer, S. Houot, F. van Oort, A. Mc Donald, as well as P. Barré. The input of B. Guenet and C. Chenu contributes to the ANR “Investissements d’avenir” programme with the reference CLAND ANR-16-CONV-0003. The input of P. Smith and C. Chenu contributes to the CIRCASA project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774378 and the projects: DEVIL (NE/M021327/1) and Soils‐R‐GRREAT (NE/P019455/1). The input of B. Grant and W. Smith was funded by Science and Technology Branch, Agriculture and Agri-Food Canada, under the scope of project J-001793. The input of A. Taghizadeh-Toosi was funded by Ministry of Environment and Food of Denmark as part of the SINKS2 project. The input of M. Abdalla contributes to the SUPER-G project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774124.Peer reviewedPostprin

Contribution of Herpesvirus Specific CD8 T Cells to Anti-Viral T Cell Response in Humans

Herpesviruses infect most humans. Their infections can be associated with pathological conditions and significant changes in T cell repertoire but evidences of symbiotic effects of herpesvirus latency have never been demonstrated. We tested the hypothesis that HCMV and EBV-specific CD8 T cells contribute to the heterologous anti-viral immune response. Volume of activated/proliferating virus-specific and total CD8 T cells was evaluated in 50 patients with acute viral infections: 20 with HBV, 12 with Dengue, 12 with Influenza, 3 with Adenovirus infection and 3 with fevers of unknown etiology. Virus-specific (EBV, HCMV, Influenza) pentamer+ and total CD8 T cells were analyzed for activation (CD38/HLA-DR), proliferation (Ki-67/Bcl-2low) and cytokine production. We observed that all acute viral infections trigger an expansion of activated/proliferating CD8 T cells, which differs in size depending on the infection but is invariably inflated by CD8 T cells specific for persistent herpesviruses (HCMV/EBV). CD8 T cells specific for other non-related non persistent viral infection (i.e. Influenza) were not activated. IL-15, which is produced during acute viral infections, is the likely contributing mechanism driving the selective activation of herpesvirus specific CD8 T cells. In addition we were able to show that herpesvirus specific CD8 T cells displayed an increased ability to produce the anti-viral cytokine interferon-γ during the acute phase of heterologous viral infection. Taken together, these data demonstrated that activated herpesvirus specific CD8 T cells inflate the activated/proliferating CD8 T cells population present during acute viral infections in human and can contribute to the heterologous anti-viral T cell response

The giant diploid faba genome unlocks variation in a global protein crop

Publisher Copyright: © 2023, The Author(s).Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.Peer reviewe