Changing the conversation about prostate cancer among African Americans: results of formative research

Objectives: To understand obstacles to and opportunities for improving prostate cancer communication to and within African American communities. Design: Researchers conducted interviews with 19 community leaders and five focus groups with healthy men and survivors. The team also conducted process evaluations of two outreach projects in which survivors spoke to African American men about prostate cancer and screening. Results: Three levels of obstacles to prostate cancer screening and treatment were identified. Individual-level obstacles included limited knowledge about the condition, about prevention and treatment, and fear of cancer. Socio-cultural barriers included distrust of the medical system, lack of a provider for routine and preventive care, reluctance to talk about cancer, and aversion to aspects of screening. Institutional deficits included the scarcity of educational efforts targeting prostate cancer. Outreach project evaluations suggested that survivors can be effective in building prostate cancer knowledge, promoting positive attitudes toward screening, and fostering conversations about prostate cancer. Educational efforts included little information about screening risks and decision-making however. Conclusions: The findings suggest that most potent interventions may combine survivor-led education with mass media and institution-based outreach. Such comprehensive programs could shift social norms that inhibit conversation and foster fear, leading in turn to more informed decisions and better treatment outcomes

Effects of patient health literacy, patient engagement and a system-level health literacy attribute on patient-reported outcomes: A representative statewide survey

BACKGROUND: The effects of health literacy are thought to be based on interactions between patients’ skill levels and health care system demands. Little health literacy research has focused on attributes of health care organizations. We examined whether the attribute of individuals’ experiences with front desk staff, patient engagement through bringing questions to a doctor visit, and health literacy skills were related to two patient-reported outcomes. METHODS: We administered a telephone survey with two sampling frames (i.e., household landline, cell phone numbers) to a randomly selected statewide sample of 3358 English-speaking adult residents of Missouri. We examined two patient-reported outcomes – whether or not respondents reported knowing more about their health and made better choices about their health following their last doctor visit. Multivariable logistic regression models were used to examine the independent contributions of predictor variables (i.e., front desk staff, bringing questions to a doctor visit, health literacy skills). RESULTS: Controlling for self-reported health, having a personal doctor, time since last visit, number of chronic conditions, health insurance, and sociodemographic characteristics, respondents who had a good front desk experience were 2.65 times as likely (95% confidence interval [CI]: 2.13, 3.30) and those who brought questions were 1.73 times as likely (95% CI: 1.32, 2.27) to report knowing more about their health after seeing a doctor. In a second model, respondents who had a good front desk experience were 1.57 times as likely (95% CI: 1.26, 1.95) and those who brought questions were 1.66 times as likely (95% CI: 1.29, 2.14) to report making better choices about their health after seeing a doctor. Patients’ health literacy skills were not associated with either outcome. CONCLUSIONS: Results from this representative statewide survey may indicate that one attribute of a health care organization (i.e., having a respectful workforce) and patient engagement through question asking may be more important to patient knowledge and health behaviors than patients’ health literacy skills. Findings support focused research to examine the effects of organizational attributes on patient health outcomes and system-level interventions that might enhance patient health

Use of natural variation reveals core genes in the transcriptome of iron-deficient Arabidopsis thaliana roots

Iron (Fe) is an essential mineral micronutrient for plants and animals. Plants respond to Fe deficiency by increasing root uptake capacity. Identification of gene networks for Fe uptake and homeostasis could result in improved crop growth and nutritional value. Previous studies have used microarrays to identify a large number of genes regulated by Fe deficiency in roots of three Arabidopsis ecotypes. However, a large proportion of these genes may be involved in secondary or genotype-influenced responses rather than in a universal role in Fe uptake or homeostasis. Here we show that a small percentage of the Fe deficiency transcriptome of two contrasting ecotypes, Kas-1 and Tsu-1, was shared with other ecotypes. Kas-1 and Tsu-1 had different timing and magnitude of ferric reductase activity upon Fe withdrawal, and different categories of overrepresented Fe-regulated genes. To gain insights into universal responses of Arabidopsis to Fe deficiency, the Kas-1 and Tsu-1 transcriptomes were compared with those of Col-0, Ler, and C24. In early Fe deficiency (24–48 h), no Fe-downregulated genes and only 10 upregulated genes were found in all ecotypes, and only 20 Fe-downregulated and 58 upregulated genes were found in at least three of the five ecotypes. Supernode gene networks were constructed to visualize conserved Fe homeostasis responses. Contrasting gene expression highlighted different responses to Fe deficiency between ecotypes. This study demonstrates the use of natural variation to identify central Fe-deficiency-regulated genes in plants, and identified genes with potential new roles in signalling during Fe deficiency

Genomic prediction for tuberculosis resistance in dairy cattle

The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates.We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data.These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies

Redundancy and the Evolution of Cis-Regulatory Element Multiplicity

The promoter regions of many genes contain multiple binding sites for the same transcription factor (TF). One possibility is that this multiplicity evolved through transitional forms showing redundant cis-regulation. To evaluate this hypothesis, we must disentangle the relative contributions of different evolutionary mechanisms to the evolution of binding site multiplicity. Here, we attempt to do this using a model of binding site evolution. Our model considers binding sequences and their interactions with TFs explicitly, and allows us to cast the evolution of gene networks into a neutral network framework. We then test some of the model's predictions using data from yeast. Analysis of the model suggested three candidate nonadaptive processes favoring the evolution of cis-regulatory element redundancy and multiplicity: neutral evolution in long promoters, recombination and TF promiscuity. We find that recombination rate is positively associated with binding site multiplicity in yeast. Our model also indicated that weak direct selection for multiplicity (partial redundancy) can play a major role in organisms with large populations. Our data suggest that selection for changes in gene expression level may have contributed to the evolution of multiple binding sites in yeast. We conclude that the evolution of cis-regulatory element redundancy and multiplicity is impacted by many aspects of the biology of an organism: both adaptive and nonadaptive processes, both changes in cis to binding sites and in trans to the TFs that interact with them, both the functional setting of the promoter and the population genetic context of the individuals carrying them

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons. A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons