The Spring 2020 Release of the Human Gene Mutation Database (HGMD) Professional is available, expanding the world’s largest collection of human inherited disease mutations to 282,895 entries–that’s 7,179 more than the previous release.
For over 30 years, HGMD Professional has been used worldwide by researchers, clinicians, diagnostic laboratories and genetic counselors as an essential tool for the annotation of next-generation sequencing (NGS) data in routine clinical and translational research. Founded and maintained by the Institute of Medical Genetics at Cardiff University, HGMD Professional provides users with a unique resource containing expert-curated mutations all backed by peer-reviewed publications where there is evidence of clinical impact.
Whether searching for an overview of known mutations associated with a particular disease, interpreting clinical test results, looking for the likely causal mutation in a list of variants, or seeking to integrate mutation content into your custom NGS pipeline or data repository—HGMD is the defacto-standard repository for heritable mutations that can be adapted to a broad range of applications.
detailed mutation reports
new mutation entries in 2019 alone
summary reports listing all known
inherited disease mutations
HGMD is powered by a team of expert curators at Cardiff University. Data are collected weekly by a combination of manual and computerized search procedures. In excess of 250 journals are scanned for articles describing germline mutations causing human genetic disease. The required data are extracted from the original articles and augmented with the necessary supporting data.
The number of disease-associated germline mutations published per year has more than doubled in the past decade (Figure 1). As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of next-generation sequencing (NGS) data.
View the complete HGMD Professional statistics here.
Read more about the importance of having access to the most up-to-date and comprehensive database for human disease mutations in our white paper.
HGMD Professional helps clinical testing labs analyze and annotate next-generation sequencing (NGS) data with current and trusted information. Unlike other mutation databases, HGMD mutations are all backed by peer-reviewed publications where there is evidence of clinical impact.
To get the most out of your HGMD Professional subscription, visit our Resources webpage for case studies, technical notes, and video tutorials. Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
An updated version of ANNOVAR is also available.
Learn more about how ANNOVAR can be used with HGMD for variant annotation. Watch a recorded webinar featuring ANNOVAR here.
The Genome Trax™ 2020.1 is now available. Updated tracks have been released with HGMD 2020.1 content for all HGMD-related tracks. Additional major updates include TRANSFAC® release 2020.1, and PROTEOME™ release 2020.1.
For labs looking to generate clinician-grade reports for germline or somatic NGS testing, QIAGEN Clinical Insight (QCI) Interpret reproducibly translates highly complex NGS data into standardized reports using current clinical evidence from the QIAGEN Knowledge Base, which consists of over 40 public and proprietary databases, including HGMD Professional.
Click here for a free demonstration of QCI Interpret.
Genetic disease is the leading cause of infant death in the United States, accounting for approximately 20% of annual infant mortality.1 Screening for genetic disease has been a long-established part of preconception and prenatal care, with a community wide screening program for Tay-Sachs disease (TSD) dating back to the 1970s; however, traditional methods of carrier screening have been offered gene-by-gene, disorder-by-disorder.
Recent developments in laboratory technologies have led to the commercial availability of expanded carrier screening (ECS) panels capable of assessing hundreds of mutations associated with genetic diseases. ECS panels have the ability to identify mutations that would otherwise not be detected. While many of the disorders on these panels are individually rare, the overall risk of having an affected offspring is 1 in 280, which is higher than the risk of having a child with a neural tube defect, for which screening is universal.2
In 2012, one of the first DNA testing and genetic counselling companies to offer ECS in the United States launched a flagship ECS panel that used next-generation sequencing (NGS) technology to assess thousands of mutations associated with more than 175 of the most relevant recessive diseases. For cancer-focused screens, the lab developed a 36 gene panel for hereditary cancer risk assessment.2
In the first three years of offering ECS, the lab screened over 400,000 individuals.3 By 2016, the lab served a network of more than 10,000 health professionals, and demand for preconception screening was soaring, owing to the increasing public awareness of the ill effects related to the transfer of genetic disease.4 Unique to the lab's ECS offering was the company’s “real-time manual curation” to support the classification of each genetic variant they encountered. Extremely thorough and highly accurate, the lab's manual literature curation enabled the company to elevate the actionable information provided to the ordering physicians and the patients they served. However, this process was labor-intensive and costly, which was ironic given the dwindling cost of DNA sequencing and the supporting technology. The question became how to scale-up without cutting corners.
Clinical decision support solutions have long been touted as the way of the future for clinical genetic testing laboratories. Combining big data analytics with advanced tools and knowledge bases, clinical decision support solutions are designed to organize, filter, and present useful information at the appropriate point in time to the person who can use it to make a decision. In 2017, the lab evaluated the use of a clinical decision support solution to help scale their genomic interpretation processes: QIAGEN Clinical Insight (QCI).*
QCI is QIAGEN’s clinical decision support solution for genetic testing laboratories. Software that reproducibly converts highly complex NGS data into clinician-ready reports, QCI is the tool through which actionable information is extracted from the sequencing results. Unlike any other clinical decision support solution on the market, QCI is largely powered by manual curation.
The knowledge base inside QCI is maintained by hundreds of Ph.D. scientists certified in clinical case curation who are committed to reading and recording all publications for a given mutation. This information is then mapped to over 2.8 million ontology classes contained within the QIAGEN Knowledge Base, providing further context by establishing relationships between variants, genes, tissue types, and pathways. When a genetic testing lab runs NGS data through QCI, the software computes the ACMG classification based on evidence curated from full-text articles, public, and private data sources. The knowledge extracted from full-text articles include observed genes, variants, function, phenotype, drug, dose, clinical cases, etc. With all this information stored in a structured knowledge base, the QIAGEN KB can quickly retrieve the relevant evidence that triggers all 28 ACMG criteria to more accurately compute an ACMG classification. Further this evidence is presented at the clinician’s fingertips for quick reference. Additionally, using natural language processing, the QIAGEN KB can auto-generate a one-sentence “finding” that is representative of the relevant evidence found in the published article.
This critical feature—automated curation of manually sourced content—saves genetic testing labs considerable time and effort when searching for variant-specific articles to satisfy the levels of evidence needed to definitively determine a classification. Especially for ECS, which is a testing practice that frequently encounters novel rare variants, the value of automation is fast becoming a necessity. To accurately and robustly appraise a novel rare variant’s pathogenicity, lab personnel must manually curate multiple lines of evidence to assess clinical significance. Therefore, if the majority of this information was autogenerated, the genomic interpretation process could be economically shortened.
The lab recognized the opportunity of integrating QCI into their curation workflow and designed a study to evaluate the concordance between the clinical evidence that QCI automatically retrieves for each observed variant classification and the clinical evidence that the lab’s curation team locates and ultimately uses in the physician reports. If the results were comparable, QCI could introduce significant time and cost savings.
The lab's manual curation workflow is outlined in Figure 1. A semi-automated process, the workflow utilizes proprietary software to initially classify variants into three categories: those with high population frequency; those that have never been reported; and those needing more information before pathogenicity can be assessed. For those remaining variants, the curation team manually searches online databases, in-house article libraries, and other available resources to find variant-specific references.
Figure 1. The lab's curation workflow
The curation workflow used to determine clinical significance of variants is summarized graphically. (a) The curation process is shown in the context of the overall laboratory workflow, in which inbound samples are eventually transformed into patient reports. (b) The curation workflow contributes lines of primary evidence that are reviewed manually, which are then combined with multiple lines of autogenerated supporting evidence to assess clinical significance.
Once evidence is collected for a variant —if any is to be found—the information is then used to assess the variant’s potential pathogenicity. As recommended by the American College of Medical Genetics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases, the lab classifies variants following a two-step process:
First, the collected evidence is categorized into one of 28 defined criteria set forth by the ACMG-AMP guidelines and assigned a code that addresses the strength of evidence, such as population data, case-control analyses, functional data, computational predictions, allelic data, segregation studies, and de novo observations. Each code is assigned a weight (stand-alone, very strong, strong, moderate, or supporting) and direction (benign or pathogenic).
Next, the lab combines these evidence codes to arrive at one of five classifications: pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), or benign (B). Important in this step is the lab's ability to modify the strength of individual criteria based on expert discretion—a safeguard that goes away with computerized systems.
To determine whether QCI could provide value to the lab’s curation team, the software was tasked with pulling a bibliography for 2,324 variants that had been recently detected by the lab’s ECS and hereditary cancer risk assessment panels. For each of these variants, the curation team had been able to match at least one published article with a specific disease-gene reference. QCI’s variant bibliography was expected to present the same quantity and quality of clinical evidence.
The study found that QCI’s variant bibliography was highly concordant with lab’s manual curation efforts. Of the 2,324 unique article-variant pairs identified by the lab, QCI pulled 2,075 of the references (89.3%) and an additional 13,938 article-variant pairs not captured by the lab's curation team.
Figure 2. Overlap of bibliographic content
Figure 2 shows the overlap in content quantity between the two sources. As depicted, QCI (QIAGEN) presents significantly more data for the evaluated variants. This outcome reflects the comprehensive nature of QIAGEN’s article-centric approach, which aims to collect all publications for a given variant. While exhaustive and not always necessary, QCI’s ability to glean information from numerous sources affords the software greater accuracy in predicting variant classifications, which is seen in the second phase of the lab's evaluation.
More important than the number of bibliographic sources, accuracy of cited content ultimately dictates clinical significance. Counsyl measured the quality of QCI’s variant bibliography by looking at how the software would classify variants based on the information it pulled. What they found was a concordance of 98.8% of the pathogenic cases (Figure 2).
During the study period, a total of 682 variants were classified as pathogenic by lab’s genetic scientists. Of these, only eight would be downgraded to VUS utilizing only QCI bibliographies. Therefore, the false negative rate for using QCI’s bibliographies was ~1.2% and is expected to decrease to <1%. Further, for a sample of 50 VUS variants examined, none would change classification with additional unique references in QCI, primarily because QCI includes secondary reports and studies for other disease contexts that may be listed as 'reviewed but not curated' in their curations.
As a result of these positive findings, QCI bibliographies have been integrated into the lab’s manual curation workflow, eliminating the need for manual searches in the majority of cases. (Left: variant-specific page in QCI). After several months, a comparison of the time taken for reference searches before and after the adoption of QCI was performed (Figure 3).
Figure 3. Before and after adopting QCI
The goal of this evaluation was to assess whether utilization of QIAGEN’s variant-specific bibliographies could match the level of accuracy and quality of the lab’s more time-intensive manual article selection approach. Investigators concluded that there are clear benefits for adopting QCI for reference identification: an exceptionally high variant-specific article coverage, and significant time savings in a search process that can take up to ~45 minutes.
The results also serve to validate the efficacy of the lab’s previous article search and selection method, with the vast majority of variant classifications being unaltered by use of QIAGEN’s bibliographies. The lab now employs QCI bibliographies for every curated variant. Consequently, manual search methods are still employed at the lab, but can now be reserved for variants nearer VUS/pathogenic evidence thresholds.
QCI has already proven a valuable resource for increasing the efficiency of the lab’s in-house curation. Work is underway to additionally incorporate QIAGEN’s continually-updated bibliographies into the automated components of our variant classification workflows: the initial software-based auto-curation step for newly-identified variants, and the identification of those requiring re-curation in response to new publications becoming available. Accordingly, we expect QCI to further contribute to the lab’s continuing efforts to improve turnaround time by increasing curation efficiency while maintaining classification accuracy in patient reports.
*Data taken from a joint study conducted by Counsyl and QIAGEN: Cox et al. ClinGen 2017. Counsyl has since been acquired.
Learn more about QIAGEN Clinical Insight for here.
References
As of March 29, 2019, HGMD contains over 256,070 germline mutations--a major achievement in our understanding of rare and hereditary disease. For years, HGMD has been recognized as the defacto standard repository for heritable mutations. Curated by experts in the field of genetics, HGMD offers information you can trust, with an unrivaled breadth of coverage. The proof is in the numbers:
256,070 expert-curated, disease-causing germline variants
10,500+ summary reports listing all known inherited disease mutations
2,600+ peer-review journals mined by experts in the field of genetics
104,000+ peer-reviewed literature reports cited
14,500+ scientific publications cite HGMD
17,000+ new mutation entries per year
View the complete HGMD statistics
Mutations may now be viewed according to whether they have additional literature evidence (browse mutations - additional literature evidence). Categories include additional functional evidence, additional phenotypes and additional case reports.
To get the most out of your HGMD subscription, please watch the video tutorials available at our Resources webpage.
New ANNOVAR databases are now available.
Learn more about how ANNOVAR can be used with HGMD for variant annotation.
Watch a recorded webinar featuring ANNOVAR here.
Updated tracks have been released with HGMD 2019.1 content for all HGMD-related tracks. Additional major updates include TRANSFAC® release 2019.1, and PROETOME™ release 2019.1.
QCI Interpret for Rare and Hereditary Disease is clinical decision support software that provides current scientific and clinical evidence to classify variants according to ACMG and ACOG interpretation guidelines.
QCI Interpret connects you to HGMD, plus 25 additional public and propriety sources. The software provides you with an expansive variant bibliography with full transparency to the underlying evidence, enabling you report confidently and scale efficiently. Learn more
An estimated 300 million people worldwide live with some form of rare disease. In the US, a disease is considered rare if it affects fewer than 200,000 people, while in the European Union, rare disease affects fewer than 1 in 2,000 people. Advances are being made in ongoing research and in initiatives and communities that support patients, and QIAGEN is pleased to once again support Rare Disease Day 2018 — the theme of which is research.
Research conquers scientific frontiers and translates genomic insights into new medicines in the rare disease community. At QIAGEN, we offer a suite of solutions that contribute to these efforts, including Biomedical Genomics Workbench, Biomedical Genomics Server, and Ingenuity Variant Analysis. We are proud that our tools are helping scientists contribute to efforts to unravel these challenging diseases.
Our tools have recently been cited by researchers in their efforts to better understand rare disease. To learn more about rare inherited cardiac disorders—the primary cause of sudden cardiac death for those below the age of 35—Anders Krogh Broendberg and his team cited CLC Genomics Workbench as one of the bioinformatics tools used to call variants in their study. At the University of Paris, Lydie Da Costa used CLC Biomedical Workbench to analyze ribosomal protein genes inherent in Diamond-Blackfan anemia, a rare congenital bone marrow failure syndrome.
QIAGEN is proud to advocate for further research to help those with rare diseases, and we stand with scientists who strive to solve these complex genetic conundrums.
The dust has settled after a whirlwind annual meeting of the American Society of Human Genetics last month. The QIAGEN team would like to thank the many scientists who stopped by our booth to learn about how our bioinformatics tools can make a difference for their projects. We spent a lot of time exploring scientific posters at the conference and came away really impressed by how much great work is being done with tools such as IPA, QIAGEN Clinical Insight (QCI), Biomedical Genomics Workbench, and more.
Thanks to our video team, we have several short clips of researchers discussing some truly fascinating scientific results. Here’s a quick tour.
Jessa Hospital used IPA to understand response to therapy for patients with Crohn’s disease and inflammatory bowel disease.
An evaluation of QCI that helped his team cut variant interpretation times by 75 percent.
Using CLC Genomics Workbench and QCI to understand variants associated with intellectual disability in children.
The challenges of interpreting variants implicated in rare disease.
Using 37-gene QIAseq panels in a wide-ranging study of pancreatic cancer.
The utility of Biomedical Genomics Workbench for analyzing QIAseq panels.
The American College of Medical Genetics and Genomics Annual Meeting (ACMG 2017) takes place on March 21-25, in Phoenix, AZ.
Mark your calendar for March 23, where one of our partners has prepared a very interesting talk on rare and inherited diseases – don’t miss it.
Title: Using NGS Bioinformatics Solutions to Compare Exomes in Rare and Inherited Diseases and Identifying the Cause of Disease
Speaker: Shimul Chowdhury, PhD, DABMGG, CGMB, Rady Children's Institute for Genomic Medicine
Date and time: March 23, Thursday, 11:05 a.m. – 11:35 a.m.
Location: Theater 2
You’re also very welcome to stop by our booth #912 where our representatives will demonstrate our solutions.
We’re looking forward to seeing you!
Learn more about this meeting from their official website - Annual Clinical Genetics Meeting
Nearly 250 million people around the world are affected by rare diseases, which are typically genetic in nature. Their rarity means that these diseases are not well understood, and funding to research and cure them is often limited. Genome sequencing has contributed to a far better characterization of rare disease by allowing scientists to home in on causal variants. For researchers who work on rare diseases, time is often the enemy. Solutions that provide fast, easy, and profound insights can significantly improve patient care. Clinical genome and exome sequencing can be integrated more broadly into the routine practice of medicine for the betterment of public health.
We are therefore thrilled to share details here about our collaboration with the Rare Genomics Institute (RG). We’ve provided RG with access to our Hereditary Disease Solution for interpreting whole exome and genome data, so that their scientists can use the tool to better understand rare diseases by identifying potential causal mutations missed by other platforms and methods. This collaboration expands their access to our genomic data interpretation tool. According to RG analyst William Chiu, “Ingenuity has a very intuitive user interface, one can easily zoom in to a short-list of potential mutations of interests in a few clicks.”
Ingenuity Variant Analysis features robust algorithms and the deeply curated QIAGEN Knowledge Base, enabling quick identification of known or novel causal variants in disease genes and discovery of novel variants or genes by leveraging pathway and network analysis.
We often think of rare diseases as being rare, affecting only a small number of people. When looked at from the perspective of a specific disease, that picture holds true. By definition a rare disease affects less than 200,000 individuals in the US or less than 1 individual in 2,000 in Europe. But the picture changes as we take a step back and consider the more than 6,000 described rare diseases as a whole. From this perspective they really aren’t so rare after all. In fact, rare diseases are estimated to affect as many as 400 million people worldwide. Furthermore, they’re incredibly diverse and complex with more than 180,000 associated mutations having been published in the scientific literature.
Watch our short video to see how easy it is to identify the published mutations for any inherited disease using HGMD. As examples we profile five rare diseases that are the subject of awareness campaigns this month:
The European Human Genetics Conference 2016 is taking place in Barcelona, Spain, on May 21-24. We'll be there and we have prepared a number of scientific activities to take place. ESHG has become one of the premier events in the field of human genetics and will set the scene for discussions about the latest developments within human and medical genetics.
You can find us at booth #550 and #552 and we encourage you to stop by for a chat, a demo, or to share your HGMD experiences on our poster-board. We'll also be presenting posters and hosting a Satellite Meeting as well.
Title: Using next-generation sequencing bioinformatics solutions to compare exomes in rare and inherited diseases and identify the cause of the disease
Speakers: Dr. Anika Joecker, PhD, Global Solution Manager, QIAGEN Bioinformatics - Céline S. Reinbold, MSc, PhD Student, Department of Biomedicine, University Hospital Basel, Switzerland - Dr. Andreas Rump, PhD, Head of Molecular genetics group, Institute of Clinical Genetics, Technical University of Dresden, Germany
Date and time: Saturday, May 21 at 12:15 p.m. - 1:45 p.m. (lunch will be available)
Join us, together with Mrs. Reinbold and Dr. Rump, for noteworthy presentations on the use of next-generation sequencing in clinical applications. We'll start the workshop with a brief introduction to our clinical genomics portfolio of solutions, presented by Dr. Joecker. Then Mrs. Reinbold will present her compelling data on a comprehensive comparison of three different exome sequencing pipelines. Dr. Rump will conclude the workshop with an exciting presentation on Exome and Mendeliome sequencing in rare genetic diseases where he will present the work from his recent publication in the Journal of Medical Genetics.
Identification of potential immune targets in controlling Endometrioid Endometrial Carcinoma metastatic progression
Presenter: Elodie Dubus
Presentation time: Sunday, May 22 at 10:15 a.m. - 11.15 a.m.
Location: Poster section 16 - Omics/Bioinformatics, poster board #P16.25A
Leveraging network analytics to infer patient syndrome and identify causal mutations using patient DNA sequence and phenotype data
Presenter: Sohela Shah
Presentation time: Sunday, May 22 at 4:45 p.m. - 5:45 p.m.
Location: Poster section P14 - New diagnostic approach, technical aspects & quality control, poster board #P14.086B
A efficient and accurate end-to-end next-generation sequencing solution for identifying and interpreting disease causing variants in rare diseases
Presenter: Anika Joecker
Presentation time: Sunday, May 22 at 4:45 p.m. - 5:45 p.m.
Location: Poster section P15 - Personalized/Predictive Medicine and Pharmacogenomics, poster board #P15.06B
QIAGEN and PreAnalytiX will host a joint Corporate Satellite where you can join us and hear how our customers are using our new technologies to advance molecular genetics research!
Title: Sample to Insight - The journey where biological samples are transformed into valuable insights
Speakers: Dr. Elena García-Arumí, Department of Clinical and Molecular Genetics and Rare Disease Unit, Hospital Vall d ́Hebron, Barcelona, Spain - Dr. Daniel Groelz, QIAGEN, Hilden, Germany
Date and time: Sunday May 22, 2016 at 11.15 a.m. – 12.45 p.m. in room 131
Dr. Elena García-Arumí, Hospital Vall d ́Hebron, will talk about molecular genetics approaches to mitochondrial OXPHOS system diseases using QIAGEN NGS strategies and Dr. Daniel Groelz, QIAGEN will present a new technology and workflow for integrated collection, stabilization, and purification of circulating cell-free DNA - the PAXgene® Blood ccfDNA System.
We're looking forward to seeing you in Barcelona!
Follow us on Twitter at @QIAGENbiox and @QIAGENscience for updates during the event
Get more details about ESHG
Human Genome Variation Society (HGVS) is hosting a meeting on "Clinical Interpretation of Variants from Next-Generation Sequencing". The meeting will take place on May 20, 2016 in Barcelona and will explore multiple aspects of the clinical use of NGS.
We're very much looking forward to participate and Dr. Sohela Shah, Principal Genome Scientist for Advanced Testing at QIAGEN Bioinformatics, will present on how our end-to-end clinical solution can benefit your work:
An efficient and accurate end-to-end solution leveraging network analytics to infer patient syndrome and identify causal mutations in rare disease cases
Session 2, 11.50 a.m. – 12.10 p.m.
Our hereditary disease solution is widely adopted, with unsurpassed comprehensiveness of validated content and accuracy. It integrates the entire analysis to insight workflow and allows you to easily analyze, discover, and interpret the causal agents of the disease.
Read more about our hereditary disease solution
Get more details about HGVS
