Adding content and functionality to the Human Gene Mutation Database (HGMD) database has further secured its role as the key global tool for genetic research.

The HGMD was first established by Cardiff University research in 1996, and is the first and only fully curated, annotated collection of inherited disease-causing mutations in nuclear genes, made up of pathologically relevant mutation data.

Since 2000, the HGMD has been developed into a valuable scientific resource and is employed worldwide by over 700 organisations in public health and commercial settings, ensuring rapid and accurate test results in both clinical diagnostics and personalised genomics.

The regular updates to the database have made it of use beyond academia, in particular of use by human molecular geneticists, genome scientists, molecular biologists, clinicians, and genetic counsellors, as well as researchers specialising in biopharmaceuticals, bioinformatics and personalised genomics.

Expansion and development

Cardiff University has licenced the HGMD to commercial partner QIAGEN, and it has now become the primary disease-associated mutation database used by the international biomedical and clinical community. QIAGEN currently has more than 600 HGMD Professional subscribers across 51 countries worldwide.

Dr Frank Schacherer, VP Products and Solutions at QIAGEN, confirmed that the customer base has continued to grow, and the compound annual growth rate of sales over the last five years was in the double digits, “thanks to the University’s commitment to keep the database current, comprehensive and competitive”.

At a national level, Genomics England (set up and owned by the Department of Health and Social Care) uses HGMD Professional to deliver the 100,000 Genomes Project. This project has sequenced 100,000 whole genomes from NHS patients with rare diseases and common cancers (around 25,000 patients), as well as their families and a control group of volunteers with no known genetic condition.

As of March 2019, potential diagnoses were identified for approximately 3,300 (1 in 5) of the rare disease sufferers enrolled in the programme, and for around 40% of those with intellectual disabilities. Clinical trials or more effective medicines were also identified for around half of the cancer patients enrolled (approximately 12,500 patients), enhancing their care and increasing the chances of survival.

The HGMD has also contributed to the development of the computational model MutPred at Cardiff University, which predicts changes in protein sequences as a consequence of genetic mutation. First published in 2009, MutPred was independently confirmed to be one of the best performing mutation pathogenicity prediction methods available. The latest version, MutPred2, was shown to identify structural and functional mutational signatures relevant to Mendelian disorders (disorders inherited through a genetic mutation in both parents, such as Duchenne Muscular Dystrophy, cystic fibrosis or sickle cell disease) as well as mutations associated with complex neurodevelopmental disorders.

To increase the usability for clinical groups and bioinformaticians, HGMD data formats have also been adapted to integrate with next-generation sequencing (NGS). NGS results can be directly compared with HGMD data, with relevant variants that have previously been implicated in disease causation highlighted. This advance in the database has improved the usability of HGMD data and greatly increased the computational analyses that could be applied, enhancing application in clinical settings.