Six previously unknown associations between specific diseases and genes have been identified by analysing databases containing the output of two genetic sequencing approaches. The research was carried out by an international group comprising members from ten medical institutes in Saudi Arabia, including KAIMRC.

The authors point out that “more than half of patients with genetic diseases remain undiagnosed,” highlighting the importance of finding new ways to establish links between genes and specific diseases. They say that genetic laboratories should be encouraged to pursue the type of database analysis they have used “for the benefit of undiagnosed patients and their families.”

The researchers analysed information from two different genetic sequencing approaches, exome and genome sequencing. Exome sequencing is a more targeted approach, determining the sequence of only the regions of DNA that are known to code for proteins. Genome sequencing, by contrast, covers the entire genome. The protein-coding exome comprises less than 2% of the genome.

The results from a genetic analysis of 38 patients suggest a clear association between variants in six genes and particular neurodevelopmental conditions or intellectual disability. Data from other patients suggests possible links between a further 31 gene variants and other diseases, including neurodevelopmental disorders, intellectual disability, oral–facial–digital syndrome, cardiomyopathies, malformation syndrome, short stature, skeletal dysplasia, and ciliary dyskinesia.

The authors explain that it is often difficult to definitively identify genes as causing or having some role in specific diseases. This challenge is complicated by the rarity of many genetic diseases, resulting in very low numbers of patients available for investigation. A third compounding factor is that even when a gene is identified as being linked to a disease, the function of the gene may not be known.

 “Our work shows the benefits of performing extended exome sequencing/genome sequencing analyses in patients with no genetic diagnosis, combined with further data repository mining,” the authors conclude. They suggest that this type of analysis become a more routine part of the work of genetic analysis laboratories rather than relying on specialised research teams.

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