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Salmonella enterica serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of S. Enteritidis infections from whole genome sequencing data. 2313 S. Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted. [ABSTRACT FROM AUTHOR]

Background: While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. Results: Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10− 7). Conclusions: Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits. [ABSTRACT FROM AUTHOR]

Genome sequencing (GS) will have a profound impact on the diagnosis of rare and inherited diseases in children and young people. We conducted 27 semi-structured interviews with young people aged 11–19 having GS through the UK 100, 000 Genomes Project. Participants demonstrated an understanding of the role and function of genes and DNA, however the terms 'genome' and 'genome sequencing' were less well understood. Participants were primarily motivated to take part to get a diagnosis or identify the gene causing their condition. The majority of participants understood they might not receive a diagnostic result. Most were unconcerned about data security or access, however anxieties existed around what the results might show and the potential for disappointment if the result was negative. Signing an assent form empowered young people, formalised the process and instilled a sense of responsibility for their choice to participate. Most young people (≥16 years) had consented to receive secondary findings and had come to that decision without parental influence. Our research suggests that at least some young people are capable of making informed decisions about taking part in GS, and that involving them in discussions about testing can empower them to take responsibility over healthcare decisions that affect them. [ABSTRACT FROM AUTHOR]