EyeG2P: an automated variant filtering approach improves efficiency of diagnostic genomic testing for inherited ophthalmic disorders.

BACKGROUND: Genomic variant prioritisation is one of the most significant bottlenecks to mainstream genomic testing in healthcare. Tools to improve precision while ensuring high recall are critical to successful mainstream clinical genomic testing, in particular for whole genome sequencing where millions of variants must be considered for each patient. METHODS: We developed EyeG2P, a publicly available database and web application using the Ensembl Variant Effect Predictor. EyeG2P is tailored for efficient variant prioritisation for individuals with inherited ophthalmic conditions. We assessed the sensitivity of EyeG2P in 1234 individuals with a broad range of eye conditions who had previously received a confirmed molecular diagnosis through routine genomic diagnostic approaches. For a prospective cohort of 83 individuals, we assessed the precision of EyeG2P in comparison with routine diagnostic approaches. For 10 additional individuals, we assessed the utility of EyeG2P for whole genome analysis. RESULTS: EyeG2P had 99.5% sensitivity for genomic variants previously identified as clinically relevant through routine diagnostic analysis (n=1234 individuals). Prospectively, EyeG2P enabled a significant increase in precision (35% on average) in comparison with routine testing strategies (p<0.001). We demonstrate that incorporation of EyeG2P into whole genome sequencing analysis strategies can reduce the number of variants for analysis to six variants, on average, while maintaining high diagnostic yield. CONCLUSION: Automated filtering of genomic variants through EyeG2P can increase the efficiency of diagnostic testing for individuals with a broad range of inherited ophthalmic disorders.

The Ensembl COVID-19 resource: ongoing integration of public SARS-CoV-2 data.

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser; the first virus to be encompassed within the Ensembl platform. This resource incorporates a new Ensembl gene set, multiple variant sets, and annotation from several relevant resources aligned to the reference SARS-CoV-2 assembly. Since the first release in May 2020, the content has been regularly updated using our new rapid release workflow, and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

Annotating and prioritizing genomic variants using the Ensembl Variant Effect Predictor-A tutorial.

The Ensembl Variant Effect Predictor (VEP) is a freely available, open-source tool for the annotation and filtering of genomic variants. It predicts variant molecular consequences using the Ensembl/GENCODE or RefSeq gene sets. It also reports phenotype associations from databases such as ClinVar, allele frequencies from studies including gnomAD, and predictions of deleteriousness from tools such as Sorting Intolerant From Tolerant and Combined Annotation Dependent Depletion. Ensembl VEP includes filtering options to customize variant prioritization. It is well supported and updated roughly quarterly to incorporate the latest gene, variant, and phenotype association information. Ensembl VEP analysis can be performed using a highly configurable, extensible command-line tool, a Representational State Transfer application programming interface, and a user-friendly web interface. These access methods are designed to suit different levels of bioinformatics experience and meet different needs in terms of data size, visualization, and flexibility. In this tutorial, we will describe performing variant annotation using the Ensembl VEP web tool, which enables sophisticated analysis through a simple interface.

Ensembl 2019.

The Ensembl project (https://www.ensembl.org) makes key genomic data sets available to the entire scientific community without restrictions. Ensembl seeks to be a fundamental resource driving scientific progress by creating, maintaining and updating reference genome annotation and comparative genomics resources. This year we describe our new and expanded gene, variant and comparative annotation capabilities, which led to a 50% increase in the number of vertebrate genomes we support. We have also doubled the number of available human variants and added regulatory regions for many mouse cell types and developmental stages. Our data sets and tools are available via the Ensembl website as well as a through a RESTful webservice, Perl application programming interface and as data files for download.

Ensembl 2018.

The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.

Ensembl 2017.

Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license.

Ensembl 2016.

The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license.

Ensembl 2015.

Ensembl (http://www.ensembl.org) is a genomic interpretation system providing the most up-to-date annotations, querying tools and access methods for chordates and key model organisms. This year we released updated annotation (gene models, comparative genomics, regulatory regions and variation) on the new human assembly, GRCh38, although we continue to support researchers using the GRCh37.p13 assembly through a dedicated site (http://grch37.ensembl.org). Our Regulatory Build has been revamped to identify regulatory regions of interest and to efficiently highlight their activity across disparate epigenetic data sets. A number of new interfaces allow users to perform large-scale comparisons of their data against our annotations. The REST server (http://rest.ensembl.org), which allows programs written in any language to query our databases, has moved to a full service alongside our upgraded website tools. Our online Variant Effect Predictor tool has been updated to process more variants and calculate summary statistics. Lastly, the WiggleTools package enables users to summarize large collections of data sets and view them as single tracks in Ensembl. The Ensembl code base itself is more accessible: it is now hosted on our GitHub organization page (https://github.com/Ensembl) under an Apache 2.0 open source license.

Ensembl 2014.

Ensembl (http://www.ensembl.org) creates tools and data resources to facilitate genomic analysis in chordate species with an emphasis on human, major vertebrate model organisms and farm animals. Over the past year we have increased the number of species that we support to 77 and expanded our genome browser with a new scrollable overview and improved variation and phenotype views. We also report updates to our core datasets and improvements to our gene homology relationships from the addition of new species. Our REST service has been extended with additional support for comparative genomics and ontology information. Finally, we provide updated information about our methods for data access and resources for user training.

Ensembl 2013.

The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat. Our resources include evidenced-based gene sets for all supported species; large-scale whole genome multiple species alignments across vertebrates and clade-specific alignments for eutherian mammals, primates, birds and fish; variation data resources for 17 species and regulation annotations based on ENCODE and other data sets. Ensembl data are accessible through the genome browser at http://www.ensembl.org and through other tools and programmatic interfaces.

Impact of tumour necrosis factor inhibitor treatment on radiographic progression in rheumatoid arthritis patients in clinical practice: results from the nationwide Danish DANBIO registry.

OBJECTIVES: To compare radiographic progression during treatment with disease-modifying antirheumatic drugs (DMARD) and subsequent treatment with tumour necrosis factor α inhibitors (TNF-I) in rheumatoid arthritis (RA) patients in clinical practice. METHODS: Conventional radiographs (x-rays) of hands and wrists were obtained ∼2 years before start (prebaseline), at baseline and ∼2 years after start (follow-up) of TNF-I. Clinical data were obtained from the DANBIO registry and the patient files. x-Rays were scored blinded to chronology according to the Sharp/van der Heijde method. Annual radiographic progression rates during the DMARD (prebaseline to baseline x-ray) and TNF-I (baseline to follow-up x-ray) periods were calculated. RESULTS: 517 RA patients (76% women, 80% IgM rheumatoid factor positive, 65% anticyclic citrullinated peptide positive, 40% current smokers, age 54 years (range 21-86), median disease duration 5 years (range 0-57)) were included. Patients were treated with infliximab (61%), etanercept (15%) or adalimumab (24%). During the DMARD period 85% of patients received methotrexate, 51% sulphasalazine and 78% prednisolone. The median DMARD period was 733 days (IQR 484-1002) and the median TNF-I period was 562 days (IQR 405-766). The median radiographic progression rate decreased from 0.7 (IQR 0-2.9) total Sharp score units/year (dTSS) in the DMARD period to 0 (0-0.9) units/year in the TNF-I period (p<0.0001, Wilcoxon). Corresponding mean dTSS values were 2.1 (SD 3.7) versus 0.7 (SD 2.3) units/year (p<0.0001, paired t test). 305 patients progressed (dTSS >0) in the DMARD period compared with 158 patients in the TNF-I period (p<0.0001, χ(2)). CONCLUSION: This nationwide observational study of RA patients documented significantly reduced radiographic progression during TNF-I treatment compared with the previous period of DMARD treatment.

Meta-analysis of heterogeneous Down Syndrome data reveals consistent genome-wide dosage effects related to neurological processes.

BACKGROUND: Down syndrome (DS; trisomy 21) is the most common genetic cause of mental retardation in the human population and key molecular networks dysregulated in DS are still unknown. Many different experimental techniques have been applied to analyse the effects of dosage imbalance at the molecular and phenotypical level, however, currently no integrative approach exists that attempts to extract the common information. RESULTS: We have performed a statistical meta-analysis from 45 heterogeneous publicly available DS data sets in order to identify consistent dosage effects from these studies. We identified 324 genes with significant genome-wide dosage effects, including well investigated genes like SOD1, APP, RUNX1 and DYRK1A as well as a large proportion of novel genes (N = 62). Furthermore, we characterized these genes using gene ontology, molecular interactions and promoter sequence analysis. In order to judge relevance of the 324 genes for more general cerebral pathologies we used independent publicly available microarry data from brain studies not related with DS and identified a subset of 79 genes with potential impact for neurocognitive processes. All results have been made available through a web server under http://ds-geneminer.molgen.mpg.de/. CONCLUSIONS: Our study represents a comprehensive integrative analysis of heterogeneous data including genome-wide transcript levels in the domain of trisomy 21. The detected dosage effects build a resource for further studies of DS pathology and the development of new therapies.

Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP.

We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P ( www.ebi.ac.uk/gene2phenotype ) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2PDD; 2044 entries). VEP-G2PDD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.

Ensembl variation resources.

The major goal of sequencing humans and many other species is to understand the link between genomic variation, phenotype and disease. There are numerous valuable and well-established variation resources, but collating and making sense of non-homogeneous, often large-scale data sets from disparate sources remains a challenge. Without a systematic catalogue of these data and appropriate query and annotation tools, understanding the genome sequence of an individual and assessing their disease risk is impossible. In Ensembl, we substantially solve this problem: we develop methods to facilitate data integration and broad access; aggregate information in a consistent manner and make it available a variety of standard formats, both visually and programmatically; build analysis pipelines to compare variants to comprehensive genomic annotation sets; and make all tools and data publicly available.

Comorbidity in multiple sclerosis is associated with diagnostic delays and increased mortality.

OBJECTIVE: To investigate the effect of chronic comorbidity on the time of diagnosis of multiple sclerosis (MS) and on mortality in MS. METHODS: We conducted a population-based, nationwide cohort study including all incident MS cases in Denmark with first MS symptom between 1980 and 2005. To investigate the time of diagnosis, we compared individuals with and without chronic comorbidity using multinomial logistic regression. To investigate mortality, we used Cox regression with time-dependent covariates, following study participants from clinical MS onset until endpoint (death) or to the end of the study, censuring at emigration. RESULTS: We identified 8,947 individuals with clinical onset of MS between 1980 and 2005. In the study of time of diagnosis, we found statistically significant odds ratios for longer diagnostic delays with cerebrovascular comorbidity (2.01 [1.44-2.80]; <0.0005), cardiovascular comorbidity (4.04 [2.78-5.87]; <0.0005), lung comorbidity (1.93 [1.42-2.62]; <0.0005), diabetes comorbidity (1.78 [1.04-3.06]; 0.035), and cancer comorbidity (2.10 [1.20-3.67]; 0.009). In the mortality study, we found higher hazard ratios with psychiatric comorbidity (2.42 [1.67-3.01]; <0.0005), cerebrovascular comorbidity (2.47 [2.05-2.79]; <0.0005), cardiovascular comorbidity (1.68 [1.39-2.03]; <0.0005), lung comorbidity (1.23 [1.01-1.50]; 0.036), diabetes comorbidity (1.39 [1.05-1.85]; 0.021), cancer comorbidity (3.51 [2.94-4.19]; <0.0005), and Parkinson disease comorbidity (2.85 [1.34-6.06]; 0.007). CONCLUSIONS: An increased awareness of both the necessity of neurologic evaluation of new neurologic symptoms in persons with preexisting chronic disease and of optimum treatment of comorbidity in MS is critical.

Inverse comorbidity in multiple sclerosis: Findings in a complete nationwide cohort.

BACKGROUND: Inverse comorbidity is disease occurring at lower rates than expected among persons with a given index disease. The objective was to identify inverse comorbidity in MS. METHODS: We performed a combined case-control and cohort study in a total nationwide cohort of cases with clinical onset of MS 1980-2005. We randomly matched each MS-case with five population controls. Comorbidity data were obtained from multiple, independent nationwide registries. Cases and controls were followed from January 1977 to the index date, and from the index date through December 2012. We controlled for false discovery rate and investigated each of eight pre-specified comorbidity categories: psychiatric, cerebrovascular, cardiovascular, lung, and autoimmune comorbidities, diabetes, cancer, and Parkinson's disease. RESULTS: A total of 8947 MS-cases and 44,735 controls were eligible for inclusion. We found no inverse associations with MS before the index date. After the index date, we found a decreased occurrence of chronic lung disease (asthma and chronic obstructive pulmonary disease) (HR 0.80 (95% CI 0.75-0.86, p<0.00025)) and overall cancer (HR 0.88 (95% CI 0.81-0.95, p=0.0005)) among MS-cases. CONCLUSION: This study showed a decreased risk of cancers and pulmonary diseases after onset of MS. Identification of inverse comorbidity and of its underlying mechanisms may provide important new entry points into the understanding of MS.

Vascular comorbidities in multiple sclerosis: a nationwide study from Denmark.

To investigate the occurrence of vascular comorbidities before and after the clinical onset of multiple sclerosis. In this combined case-control and cohort study, all Danish born citizens with onset of multiple sclerosis 1980-2005 were identified from the Danish Multiple Sclerosis Registry and randomly matched with controls regarding year of birth, gender, and municipality on January 1st in the year of multiple sclerosis (MS) onset (index date). Individual-level information on comorbidities was obtained from several independent nationwide registries and linked to the study population by unique personal identification numbers. To assess the presence of vascular comorbidities before and after MS onset, cases and controls were followed from January 1977 to the index date, and from the index date through December 2012. We used logistic regression to calculate odds ratios (ORs) and Cox regression to calculate hazard ratios (HRs). Before the index date, MS cases had a decreased probability for cerebrovascular comorbidity [OR 0.69 (95 % CI 0.48-0.99, p = 0.043)], and a numerically but not statistically significant decreased probability for cardiovascular comorbidity [OR 0.87 (95 % CI 0.71-1.07, p = 0.188)]. After the index date, MS cases had an increased risk for cerebrovascular comorbidity [HR 1.84 (95 % CI 1.69-2.00, p < 0.0005)], and for cardiovascular comorbidity [HR 1.08 (95 % CI 1.02-1.15, p = 0.013)]. The lower occurrence of cerebrovascular comorbidities in cases prior to MS onset could be due to protective immune mechanisms, while the higher occurrence of vascular comorbidities in cases after MS onset could be because of converging causal pathways of the coexisting diseases. These findings deserve to be studied closer in a broader spectrum of comorbidities in MS.

The Ensembl Variant Effect Predictor.

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

Establishment of age- and sex-adjusted reference data for hand bone mass and investigation of hand bone loss in patients with rheumatoid arthritis treated in clinical practice: an observational study from the DANBIO registry and the Copenhagen Osteoarthritis Study.

BACKGROUND: Rheumatoid arthritis is characterised by progressive joint destruction and loss of periarticular bone mass. Hand bone loss (HBL) has therefore been proposed as an outcome measure for treatment efficacy. A definition of increased HBL adjusted for age- and sex-related bone loss is lacking. In this study, we aimed to: 1) establish reference values for normal hand bone mass (bone mineral density measured by digital x-ray radiogrammetry (DXR-BMD)); and 2) examine whether HBL is normalised in rheumatoid arthritis patients during treatment with tumour necrosis factor alpha inhibitors (TNFI). METHODS: DXR-BMD was measured from hand x-rays in a reference cohort (1485 men/2541 women) without arthritis randomly selected from an urban Danish population. Sex- and age-related HBL/year was estimated. DXR-BMD was measured in rheumatoid arthritis patients (n = 350: at start of TNFI, and ~2 years after TNFI start), of which 135 patients had three x-rays (~2 years prior to TNFI, at start of TNFI, and ~2 years after TNFI start). Individual HBL/year prior to and during TNFI was calculated and compared to reference values. RESULTS: Estimated HBL/year varied strongly with age and sex. Compared to the reference values, 75 % of 135 patients had increased HBL prior to TNFI treatment and 59 % had increased HBL during TNFI treatment (p = 0.17, Chi-squared). In 38 % (38/101) of patients with increased HBL, HBL was normalised during TNFI treatment, whereas 47 % (16/34) of patients with normal HBL prior to TNFI had increased HBL during TNFI treatment. In the 350 patients, increased HBL during TNFI was associated with time-averaged 28-joint disease activity score (odds ratio 1.69 (95 % Confidence Interval 1.34-2.15)/unit increase, p < 0.001), and patients in time-averaged remission had lower HBL than patients without remission (0.0032 vs. 0.0058 g/cm(2)/year; p < 0.001, Mann-Whitney). CONCLUSIONS: We established age- and sex-specific reference values for DXR-BMD in a large cohort without arthritis. HBL was increased in the majority of rheumatoid arthritis patients initiating TNFI in clinical practice, and only normalised in a minority during TNFI.

Which factors influence radiographic progression during treatment with tumor necrosis factor inhibitors in clinical practice? Results from 930 patients with rheumatoid arthritis in the nationwide Danish DANBIO registry.

OBJECTIVE: To investigate baseline characteristics associated with radiographic progression and the effect of disease activity, drug, switching, and withdrawal on radiographic progression in tumor necrosis factor (TNF) inhibitor-naive patients with rheumatoid arthritis (RA) followed for about 2 years after anti-TNF initiation in clinical practice. METHODS: DANBIO-registered patients with RA who had available radiographs (anti-TNF initiation and ∼2 yrs followup) were included. Radiographs were scored, blinded to chronology with the Sharp/van der Heijde method and linked with DANBIO data. Baseline characteristics were investigated with univariate regression and significant variables included in a multivariable logistic regression analysis with ± radiographic progression [Δ total Sharp score (TSS) > 0] as dependent variable. Effect of time-averaged C-reactive protein (CRP), 28-joint Disease Activity Score with CRP (DAS28-CRP), and treatment status at followup were investigated with univariate regression analysis. RESULTS: The study included 930 patients. They were 75% women, 79% positive for IgM-rheumatoid factor (IgM-RF), median age was 57 yrs (range 19-88), disease duration 9 yrs (1-59), DAS28-CRP 5.0 (1.4-7.8), TSS median 15 [3-45 interquartile range (IQR)] and mean 31 (SD 40). Patients started treatment with infliximab (59%), etanercept (18%), or adalimumab (23%). At followup (median 526 days, IQR 392-735), 61% were treated with the initial anti-TNF, 29% had switched TNF inhibitor, and 10% had withdrawn. Twenty-seven percent of patients had progressed radiographically. ΔTSS was median 0.0 [0.0-0.5 IQR/mean 0.6 (SD 2.4)] units/year. Higher TSS, older age, positive IgM-RF, and concomitant prednisolone at baseline were associated with radiographic progression. Time-averaged DAS28-CRP and time-averaged CRP, but not type of TNF inhibitor, were associated with radiographic progression. Patients who stopped/switched during followup progressed more than patients who continued treatment. CONCLUSION: High TSS, older age, IgM-RF positivity, and concomitant prednisolone were associated with radiographic progression during 2 years of followup of 930 anti-TNF-treated patients with RA in clinical practice. High disease activity and switching/stopping anti-TNF treatment were associated with radiographic progression.