Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

BACKGROUND: We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control. RESULTS: The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and > 3,000,000 k-mers, indicating adequate performance of the algorithms used. CONCLUSIONS: To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC

Foxa1 Reduces Lipid Accumulation in Human Hepatocytes and Is Down-Regulated in Nonalcoholic Fatty Liver

Triglyceride accumulation in nonalcoholic fatty liver (NAFL) results from unbalanced lipid metabolism which, in the liver, is controlled by several transcription factors. The Foxa subfamily of winged helix/forkhead box (Fox) transcription factors comprises three members which play important roles in controlling both metabolism and homeostasis through the regulation of multiple target genes in the liver, pancreas and adipose tissue. In the mouse liver, Foxa2 is repressed by insulin and mediates fasting responses. Unlike Foxa2 however, the role of Foxa1 in the liver has not yet been investigated in detail. In this study, we evaluate the role of Foxa1 in two human liver cell models, primary cultured hepatocytes and HepG2 cells, by adenoviral infection. Moreover, human and rat livers were analyzed to determine Foxa1 regulation in NAFL. Results demonstrate that Foxa1 is a potent inhibitor of hepatic triglyceride synthesis, accumulation and secretion by repressing the expression of multiple target genes of these pathways (e.g., GPAM, DGAT2, MTP, APOB). Moreover, Foxa1 represses the fatty acid transporter protein FATP2 and lowers fatty acid uptake. Foxa1 also increases the breakdown of fatty acids by inducing peroxisomal fatty acid β-oxidation and ketone body synthesis. Finally, Foxa1 is able to largely up-regulate UCP1, thereby dissipating energy and consistently decreasing the mitochondria membrane potential. We also report that human and rat NAFL have a reduced Foxa1 expression, possibly through a protein kinase C-dependent pathway. We conclude that Foxa1 is an antisteatotic factor that coordinately tunes several lipid metabolic pathways to block triglyceride accumulation in hepatocytes. However, Foxa1 is down-regulated in human and rat NAFL and, therefore, increasing Foxa1 levels could protect from steatosis. Altogether, we suggest that Foxa1 could be a novel therapeutic target for NAFL disease and insulin resistance

Does organ donation legislation affect individuals' willingness to donate their own or their relative's organs?: evidence from European Union survey data

Background Maintaining adequately high organ donation rates proves essential to offering patients all appropriate and available treatment options. However, the act of donation is in itself an individual decision that requires a depth of understanding that interacts with the social setting and the institutional framework into which an individual is embedded. This study contributes to understanding factors driving organ donation rates by examining how country regulation, individuals' awareness of regulatory setting, social interactions and socio-demographic determinants influence individuals' willingness to donate their own organs or those of a relative. Methods We draw representative data from the Eurobarometer survey 58.2 undertaken in 2002 with respondents throughout the European Union to capture heterogeneity in institutional setting. We use logistic regression techniques to estimate the determinants of willingness to donate one's own organs and those of a deceased relative. We employ interaction terms to examine the relationship between institutional setting and respondent's awareness of organ donation legislation in their country. Results Our findings indicate that individuals are more likely to donate their organs than to consent to the donation of a relative's organs. Both decisions are affected by regulation (presumed consent), awareness of regulation and social interactions such as the ability to count on others in case of a serious problem (reciprocity). Furthermore, education (more educated), age (younger), expressing some sort of political affiliation determine willingness to donate one's own organs and consent to the donation of those of a relative. Conclusion This study confirms and develops further previous research findings that presumed consent organ donation policy positively affects the willingness of individuals to donate their own organs and those of relative by highlighting the importance of awareness of this regulation and an individual's level of social interactions in making choices about donation. Results found using interaction terms underline the importance of population awareness of organ donation legislation as well as the legislation type itself. Findings also point to the role of social interactions in influencing individuals' willingness to donate their organs or those of a relative

Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

BACKGROUND: We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control. RESULTS: The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and > 3,000,000 k-mers, indicating adequate performance of the algorithms used. CONCLUSIONS: To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC

Additional file 4 of Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

Additional file 4. Genomes and phenotypic data used in GWAS. The phenotypic patient data used for the GWAS, including accession numbers of the genomes of the infected isolates are depicted in this table