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Genomics study uses UK Biobank Data to reveal new genetic associations for rare diseases

Written by Skel Yeung

Rare diseases affect up to 10% of the global population. Yet the majority of rare diseases have not been extensively researched. Even fewer have effective treatments. But there are new avenues opening up that will help. One such avenue is the leveraging of biobanks and the use of phenotype mapping to improve our knowledge of rare diseases. A recent study published by Genome Medicine has found a way to create a mapping approach that could elucidate the demographics and genetic associations of rare diseases, thereby producing a unique population assay for rare diseases in the general population.

Enhancing rare disease mapping

Biobanks have become a vital resource in medical research. Population-based biobanks, like the UK biobank (UKB), store biological information on individuals with both common and rare diseases. Nevertheless, it can be difficult to utilize their diagnosis coding system – the ICD-10 as it is not specifically designed for rare diseases.

Therefore, to enhance rare disease mapping, researchers performed consensus mapping of ICD-10 to ORPHA codes. This identified which ICD-10 codes indicated rare diseases, using them to catalogue data through the UKB. Other analyses were also conducted, such as the investigation of comorbidities in individuals with different groups of rare diseases and an exome sequencing analysis on individuals with European ancestry. The findings were uploaded onto an interactive website to aid other investigations into rare disease.

Novel insights into rare disease

The study identified that 23,575 individuals in the UKB (~5%) were found to have at least one of 420 specific rare diseases, with 2,602 individuals having more than one rare disease (~10%). This highlights the prevalence of comorbidities in individuals with rare diseases – suggesting that some of these conditions could be related, either due to similar molecular mechanisms or by chance.

The study also identified significant genetic associations for rare disease. The gene JAK2 V617F was shown to be associated with immune thrombocytopenic purpura, a blood disorder characterised by low platelet levels. For essential thrombocythemia, a rare disease which causes the body to produce too many platelets, a new CALR loss of function variant was identified. CALR is a gene that codes for the protein calreticulin, which is found throughout the cell acting as a molecular chaperone, sequestering misfolded proteins.

The demographics of individuals with rare diseases were also analysed, and results show that individuals with rare diseases have a slightly higher average age (60) than those without (58). However, there were considerable differences in the prevalence of rare diseases between males and females. For instance, digestive system rare diseases are more common in males. Meanwhile, rare musculoskeletal and skin diseases are more frequent among females.

Limitations and future steps

Despite successful efforts in creating enhanced rare disease mapping, limitations still remain for those using the ICD-10 diagnosis coding system. The study states that a single ICD-10 code can describe multiple diseases, so it is not always clear which disease an individual has, nor whether that disease is rare. Nevertheless, coding systems and rare disease research are ever-evolving, and the researchers stated plans to repeat this mapping approach on ICD-11 once it becomes widely implemented.

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Biobank / Rare Diseases

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