An estimated 3.5 million people in the UK live with one of the over 7,000 known rare diseases, a substantial proportion of whom face long delays in receiving an accurate diagnosis. Symptoms may be non-specific, overlap with more common conditions, or vary significantly between patients, resulting in rare disease patients on average receiving three misdiagnoses and consulting with five doctors before receiving an accurate diagnosis. The EU Regulation on Orphan Medicinal Products defines a disease as rare if it affects no more than 1 in 2,000 people in the European population, making accurate prevalence (i.e. the number of people in a given population who have a specific disease at a particular point in time) data extremely important when developing healthcare policies for patients with rare diseases and informing R&D investment regarding the development of new drugs.
Despite this, accurate prevalence estimates can be difficult to obtain for rare diseases. Data are derived from multiple sources of information which may not be easily combined, such as case reports, patient registries and systematic reviews, and this is compounded by the potential for different studies to use different diagnostic criteria and methods for case ascertainment.
The primary aim of this project is to use the UK Biobank dataset to produce more accurate calculations of rare genetic disease prevalence, with a secondary aim to assess the characteristics of rare disease patients (such as sex, socioeconomic status and ethnicity) to determine whether any of these groups are especially prone to underdiagnosis compared to others.
This work has the potential to be hugely impactful to public health. Expected prevalence figures calculated using genetic databases can help to quantify the ‘hidden population’ who are affected by a rare disease but have not received a diagnosis. This information can in turn be used to more accurately calculate the future health and economic burden of these diseases, which is critical information to inform pharmaceutical development for rare genetic diseases. Improved prevalence estimates can also highlight these diseases to clinicians and may reduce misdiagnoses, allowing earlier intervention and treatment / management of these conditions.
We estimate that the research programme outlined in this project proposal will take 36 months to complete.
