During COVID-19, diagnostic serological tools and vaccines have been developed. To inform control activities in a post-vaccine surveillance setting, we have developed an online "immuno-analytics" resource that combines epitope, sequence, protein and SARS-CoV-2 mutation analysis. SARS-CoV-2 spike and nucleocapsid proteins are both vaccine and serological diagnostic targets. Using the tool, the nucleocapsid protein appears to be a sub-optimal target for use in serological platforms. Spike D614G (and nsp12 L314P) mutations were most frequent (> 86%), whilst spike A222V/L18F have recently increased. Also, Orf3a proteins may be a suitable target for serology. The tool can accessed from: http://genomics.lshtm.ac.uk/immuno (online); https://github.com/dan-ward-bio/COVID-immunoanalytics (source code).

Erratum in Genome Med. 2021 Jul 5;13(1):109.

BACKGROUND: Identifying essential genes in genome-wide loss-of-function screens is a critical step in functional genomics and cancer target finding. We previously described the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm for accurate classification of gene essentiality from short hairpin RNA and CRISPR/Cas9 genome-wide genetic screens. RESULTS: We introduce an updated version, BAGEL2, which employs an improved model that offers a greater dynamic range of Bayes Factors, enabling detection of tumor suppressor genes; a multi-target correction that reduces false positives from off-target CRISPR guide RNA; and the implementation of a cross-validation strategy that improves performance ~ 10× over the prior bootstrap resampling approach. We also describe a metric for screen quality at the replicate level and demonstrate how different algorithms handle lower quality data in substantially different ways. CONCLUSIONS: BAGEL2 substantially improves the sensitivity, specificity, and performance over BAGEL and establishes the new state of the art in the analysis of CRISPR knockout fitness screens. BAGEL2 is written in Python 3 and source code, along with all supporting files, are available on github ( https://github.com/hart-lab/bagel ).

BACKGROUND: The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS: Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS: We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS: APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

Clinical use of polygenic risk scores (PRS) will look very different to the more familiar monogenic testing. Here we argue that despite these differences, most of the ethical, legal, and social issues (ELSI) raised in the monogenic setting, such as the relevance of results to family members, the approach to secondary and incidental findings, and the role of expert mediators, continue to be relevant in the polygenic context, albeit in modified form. In addition, PRS will reanimate other old debates. Their use has been proposed both in the practice of clinical medicine and of public health, two contexts with differing norms. In each of these domains, it is unclear what endpoints clinical use of PRS should aim to maximize and under what constraints. Reducing health disparities is a key value for public health, but clinical use of PRS could exacerbate race-based health disparities owing to differences in predictive power across ancestry groups. Finally, PRS will force a reckoning with pre-existing questions concerning biomarkers, namely the relevance of self-reported race, ethnicity and ancestry, and the relationship of risk factors to disease diagnoses. In this Opinion, we argue that despite the parallels to the monogenic setting, new work is urgently needed to gather data, consider normative implications, and develop best practices around this emerging branch of genomics.

BACKGROUND: Several polygenic risk scores (PRS) have been developed for cardiovascular risk prediction, but the additive value of including PRS together with conventional risk factors for risk prediction is questionable. This study assesses the clinical utility of including four PRS generated from 194, 46K, 1.5M, and 6M SNPs, along with conventional risk factors, to predict risk of ischemic heart disease (IHD), myocardial infarction (MI), and first MI event on or before age 50 (early MI). METHODS: A cross-validated logistic regression (LR) algorithm was trained either on ~ 440K European ancestry individuals from the UK Biobank (UKB), or the full UKB population, including as features different combinations of conventional established-at-birth risk factors (ancestry, sex) and risk factors that are non-fixed over an individual's lifespan (age, BMI, hypertension, hyperlipidemia, diabetes, smoking, family history), with and without also including PRS. The algorithm was trained separately with IHD, MI, and early MI as prediction labels. RESULTS: When LR was trained using risk factors established-at-birth, adding the four PRS significantly improved the area under the curve (AUC) for IHD (0.62 to 0.67) and MI (0.67 to 0.73), as well as for early MI (0.70 to 0.79). When LR was trained using all risk factors, adding the four PRS only resulted in a significantly higher disease prevalence in the 98th and 99th percentiles of both the IHD and MI scores. CONCLUSIONS: PRS improve cardiovascular risk stratification early in life when knowledge of later-life risk factors is unavailable. However, by middle age, when many risk factors are known, the improvement attributed to PRS is marginal for the general population.

BACKGROUND: Gastric cancer (GC) is a heterogenous disease consisted of several subtypes with distinct molecular traits. The clinical implication of molecular classification has been limited especially in association with treatment efficacy of ramucirumab or various targeted agents. METHODS: We conducted a prospective non-randomized phase II single-arm trial of ramucirumab plus paclitaxel as second-line chemotherapy in 62 patients with metastatic GC who failed to respond to first-line fluoropyrimidine plus platinum treatment. For integrative molecular characterization, all patients underwent pre-ramucirumab treatment tissue biopsy for whole-exome/whole-transcriptome sequencing to categorize patients based on molecular subtypes. We also systematically performed integrative analysis, combining genomic, transcriptomic, and clinical features, to identify potential molecular predictors of sensitivity and resistance to ramucirumab treatment. RESULTS: Sixty-two patients were enrolled in this study between May 2016 and October 2017. Survival follow-up in all patients was completed as of the date of cut-off on January 2, 2019. No patient attained complete response (CR), while 22 patients achieved confirmed partial response (PR), resulting in a response rate (RR) of 35.5% (95% CI, 23.6-47.4). According to TCGA molecular classification, there were 30 GS, 18 CIN, 3 EBV, and 0 MSI tumors. The RR was 33% in GS (10/30), 33% in CIN (6/18), and 100% in EBV-positive GC patients with significant statistical difference for EBV(+) against EBV(-) tumors (P = 0.016; chi-squared test). Moreover, responsive patients were marked by activation of angiogenesis, VEGF, and TCR-associated pathways, while non-responder patients demonstrated enrichments of sonic hedgehog signaling pathway and metabolism activity. Integrative multi-layer data analysis further identified molecular determinants, including EBV status, and somatic mutation in GNAQ to ramucirumab activity. CONCLUSIONS: Prospective molecular characterization identified a subset of GC patients with distinct clinical response to ramucirumab therapy, and our results demonstrate the feasibility of personalized therapeutic opportunities in gastric cancer. TRIAL REGISTRATION: The study was registered on ClinicalTrial.gov ( NCT02628951 ) on June 12, 2015.

Personalised dietary modulation of the gut microbiota may be key to disease management. Current investigations provide a broad understanding of the impact of diet on the composition and activity of the gut microbiota, yet detailed knowledge in applying diet as an actionable tool remains limited. Further to the relative novelty of the field, approaches are yet to be standardised and extremely heterogeneous research outcomes have ensued. This may be related to confounders associated with complexities in capturing an accurate representation of both diet and the gut microbiota. This review discusses the intricacies and current methodologies of diet-microbial relations, the implications and limitations of these investigative approaches, and future considerations that may assist in accelerating applications. New investigations should consider improved collection of dietary data, further characterisation of mechanistic interactions, and an increased focus on -omic technologies such as metabolomics to describe the bacterial and metabolic activity of food degradation, together with its crosstalk with the host. Furthermore, clinical evidence with health outcomes is required before therapeutic dietary strategies for microbial amelioration can be made. The potential to reach detailed understanding of diet-microbiota relations may depend on re-evaluation, progression, and unification of research methodologies, which consider the complexities of these interactions.

BACKGROUND: Enterococcus faecium is a commensal of the gastrointestinal tract of animals and humans but also a causative agent of hospital-acquired infections. Resistance against glycopeptides and to vancomycin has motivated the inclusion of E. faecium in the WHO global priority list. Vancomycin resistance can be conferred by the vanA gene cluster on the transposon Tn1546, which is frequently present in plasmids. The vanA gene cluster can be disseminated clonally but also horizontally either by plasmid dissemination or by Tn1546 transposition between different genomic locations. METHODS: We performed a retrospective study of the genomic epidemiology of 309 vancomycin-resistant E. faecium (VRE) isolates across 32 Dutch hospitals (2012-2015). Genomic information regarding clonality and Tn1546 characterization was extracted using hierBAPS sequence clusters (SC) and TETyper, respectively. Plasmids were predicted using gplas in combination with a network approach based on shared k-mer content. Next, we conducted a pairwise comparison between isolates sharing a potential epidemiological link to elucidate whether clonal, plasmid, or Tn1546 spread accounted for vanA-type resistance dissemination. RESULTS: On average, we estimated that 59% of VRE cases with a potential epidemiological link were unrelated which was defined as VRE pairs with a distinct Tn1546 variant. Clonal dissemination accounted for 32% cases in which the same SC and Tn1546 variants were identified. Horizontal plasmid dissemination accounted for 7% of VRE cases, in which we observed VRE pairs belonging to a distinct SC but carrying an identical plasmid and Tn1546 variant. In 2% of cases, we observed the same Tn1546 variant in distinct SC and plasmid types which could be explained by mixed and consecutive events of clonal and plasmid dissemination. CONCLUSIONS: In related VRE cases, the dissemination of the vanA gene cluster in Dutch hospitals between 2012 and 2015 was dominated by clonal spread. However, we also identified outbreak settings with high frequencies of plasmid dissemination in which the spread of resistance was mainly driven by horizontal gene transfer (HGT). This study demonstrates the feasibility of distinguishing between modes of dissemination with short-read data and provides a novel assessment to estimate the relative contribution of nested genomic elements in the dissemination of vanA-type resistance.

BACKGROUND: Shigella is a major diarrheal pathogen for which there is presently no vaccine. Whole genome sequencing provides the ability to predict and derive novel antigens for use as vaccines. Here, we aimed to identify novel immunogenic Shigella antigens that could serve as Shigella vaccine candidates, either alone, or when conjugated to Shigella O-antigen. METHODS: Using a reverse vaccinology approach, where genomic analysis informed the Shigella immunome via an antigen microarray, we aimed to identify novel immunogenic Shigella antigens. A core genome analysis of Shigella species, pathogenic and non-pathogenic Escherichia coli, led to the selection of 234 predicted immunogenic Shigella antigens. These antigens were expressed and probed with acute and convalescent serum from microbiologically confirmed Shigella infections. RESULTS: Several Shigella antigens displayed IgG and IgA seroconversion, with no difference in sero-reactivity across by sex or age. IgG sero-reactivity to key Shigella antigens was observed at birth, indicating transplacental antibody transfer. Six antigens (FepA, EmrK, FhuA, MdtA, NlpB, and CjrA) were identified in in vivo testing as capable of producing binding IgG and complement-mediated bactericidal antibody. CONCLUSIONS: These findings provide six novel immunogenic Shigella proteins that could serve as candidate vaccine antigens, species-specific carrier proteins, or targeted adjuvants.

Author information: (1)Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. (2)PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany. (3)Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany. (4)Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands. (5)4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece. (6)Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany. (7)1st Department of Pulmonary Medicine and Intensive Care Unit, National and Kapodistrian University of Athens, Medical School, Athens, Greece. (8)West German Genome Center (WGGC), University of Bonn, Bonn, Germany. (9)Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands. (10)Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. (11)Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. (12)Department of Internal Medicine II, Section of Pneumology, University Hospital of Bonn (UKB), Bonn, Germany. (13)Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany. (14)Immunology & Metabolism, Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany. (15)Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany. (16)German Center for Infection Research (DZIF), Bonn, Germany. (17)Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. t.ulas@uni-bonn.de. (18)PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany. t.ulas@uni-bonn.de.

BACKGROUND: Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations. METHODS: A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center's (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank. RESULTS: Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB. CONCLUSIONS: Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.

BACKGROUND: Ebola virus disease (EVD) is an often-fatal infection where the effectiveness of medical countermeasures is uncertain. During the West African outbreak (2013-2016), several patients were treated with different types of anti-viral therapies including monoclonal antibody-based cocktails that had the potential to neutralise Ebola virus (EBOV). However, at the time, the efficacy of these therapies was uncertain. Given the scale of the outbreak, several clinical phenotypes came to the forefront including the ability of the same virus to cause recrudescence in the same patient-perhaps through persisting in immune privileged sites. Several key questions remained including establishing if monoclonal antibody therapy was effective in humans with severe EVD, whether virus escape mutants were selected during treatment, and what is the potential mechanism(s) of persistence. This was made possible through longitudinal samples taken from a UK patient with EVD. METHODS: Several different sample types, plasma and cerebrospinal fluid, were collected and sequenced using Illumina-based RNAseq. Sequence reads were mapped both to EBOV and the human genome and differential gene expression analysis used to identify changes in the abundance of gene transcripts as infection progressed. Digital Cell Quantitation analysis was used to predict the immune phenotype in samples derived from blood. RESULTS: The findings were compared to equivalent data from West African patients. The study found that both virus and host markers were predictive of a fatal outcome. This suggested that the extensive supportive care, and most likely the application of the medical countermeasure ZMab (a monoclonal antibody cocktail), contributed to survival of the UK patient. The switch from progression to a 'fatal' outcome to a 'survival' outcome could be seen in both the viral and host markers. The UK patient also suffered a recrudescence infection 10 months after the initial infection. Analysis of the sequencing data indicated that the virus entered a period of reduced or minimal replication, rather than other potential mechanisms of persistence-such as defective interfering genomes. CONCLUSIONS: The data showed that comprehensive supportive care and the application of medical countermeasures are worth pursuing despite an initial unfavourable prognosis.