As the global population approaches 9.7 billion inhabitants by the year 2050, humanity faces enormous challenges to feed, house, and provide basic living requirements for the growing population while preserving the health of wildlife and the ecosystem. Dairy source foods play an important part in providing nutrient and energy dense sources of calories and establishing Bifidobacterium as a keystone species in the gut for positive health outcomes in infants and children. In developed countries, dairy products have a high food safety record when pasteurized and properly processed. However, when milk is consumed unpasteurized, as often occurs in developing countries where regulation and oversight of the dairy industry is lacking, dairy can serve as a vector for zoonotic transmission of disease and can contain adulterants such as antibiotic residues. Here we provide an overview for the importance of dairy source foods for nutrition and with a One Health perspective and discuss the historical events that have resulted in a high standard of dairy food safety in the United States. This review article covers the Origins of One Health, the role of milk in transmission of disease, management practices and regulations to ensure safe dairy products reach consumers, current challenges facing the dairy industry and impacts on public health, and how these standards can be employed in low and middle income countries to improve public health, nutrition and economic benefits to farmers.

This article recounts a narrative of professional transformation inspired by the works of Paulo Freire and Gloria Ladson-Billings and advanced by a participatory action research (PAR) project. The PAR team for this case study, consisting of the university teacher educator as a “coach” and a high school classroom teacher along with her students, examines the use of community-based knowledge in a form of corrido (ballads) studies. In this process, the ballads become the basis for learners’ engagement with literacy activities in the context of what is known as a heritage language Spanish class. The analysis focuses on the process of designing a culturally relevant pedagogy and ensuring its effectiveness through the examination of pre- and postwriting samples and students’ fluid identification with various ethnic labels.

In Rwanda, cattle and milk hold a cultural and historical significance, providing an opportunity for pro-dairy governmental policies aimed to alleviate food insecurity, malnutrition, and improve livelihoods. The government of Rwanda has identified strategies to grow the dairy sector through strategic investment to achieve these goals. It is estimated two-thirds of lactating cows in Rwanda have clinical or subclinical mastitis, which reduces milk production and increases the risk of milk as a source for zoonotic disease if the milk is consumed undercooked or unpasteurized. This case study outlines the implementation of a One Health framework that integrates education, research, and outreach in Rwanda to improve food safety and food security, for the social, economic, and health benefit of Rwandans and their livestock. Twenty-five Rwandan Extension Specialists participated in the Dairy Dynamic Management education, research, and outreach program. Once trained, the extension specialists supported 30 small holder dairy farmers in performing proper husbandry and animal health practices for mastitis control and reduction of bacterial counts in the udder. Over the 16-week program, 30 small holder dairy farmers and 100 dairy cows were surveyed weekly for animal husbandry, animal health, and mastitis indicators. Outcomes were evaluated by monitoring animal health, foodborne pathogens in milk, and compliance to animal husbandry protocols. Quarter milk samples were collected weekly and evaluated for the presence of bacteria that are common causes of mastitis. We found a statistically significant reduction of mean total bacterial counts and prevalence of bacterial species in quarters over the 16-week training (P ≤ .01). Smallholders were monitored through observing farmers performing hygienic milking protocols. Farmers conducted the protocol correctly greater than 90% of the time by the end of the 16-week program for 5 of 7 steps for proper hygienic milking procedures, indicating farmers were eager to learn and adopt the procedures. However, follow-up and retraining with Extension Specialists is vital to continued success. We demonstrate that an integrative One Health education, research, and outreach program can be successful in improving animal health, food safety, and food security and this framework can be applied to other agricultural sectors and geographic regions.

Rhabdomyosarcoma (RMS) is a common childhood cancer that shares features with developing skeletal muscle. Yet, the conservation of cellular hierarchy with human muscle development and the identification of molecularly defined tumor-propagating cells has not been reported. Using single-cell RNA-sequencing, DNA-barcode cell fate mapping and functional stem cell assays, we uncovered shared tumor cell hierarchies in RMS and human muscle development. We also identified common developmental stages at which tumor cells become arrested. Fusion-negative RMS cells resemble early myogenic cells found in embryonic and fetal development, while fusion-positive RMS cells express a highly specific gene program found in muscle cells transiting from embryonic to fetal development at 7-7.75 weeks of age. Fusion-positive RMS cells also have neural pathway-enriched states, suggesting less-rigid adherence to muscle-lineage hierarchies. Finally, we identified a molecularly defined tumor-propagating subpopulation in fusion-negative RMS that shares remarkable similarity to bi-potent, muscle mesenchyme progenitors that can make both muscle and osteogenic cells.

Objectives

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

Design

Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

Setting

Multiple institutions that were members of international PRACTICAL consortium.

Participants

All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

Main outcome measures

Prediction with hazard score of age of onset of aggressive cancer in validation set.

Results

In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10^-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

Conclusions

Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR_98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR_98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR_98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

Background

A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.

Methods

United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.

Results

The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.

Conclusions

PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.

Impact

Personalized genetic risk assessments could inform prostate cancer screening decisions.

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.