Exploiting the Power of NGS to Diagnose Rare Diseases

dna rare disease ngs diploid

Diploid (Belgium) is using genome sequencing data to diagnose rare diseases – and is now charging only if its algorithms can match the genome to a specific rare disease.

diploid_logo_rare_disease_ngsPatients of rare diseases often struggle with the lack of therapies options – an empty space where Biotechs seem to thrive. But therapy availability is not the only problem. Because these diseases are rare, they are often underdiagnosed…

The more typical method of analysing this type of genetic defects is Comparative Genomic Hybridization arrays (aCGH). This tool indicates if a patient has more or less genetic material than healthy DNA, and in what areas of the patient’s genome.

Whole genome shotgun (WGS) analysis can make diagnostics of rare diseases easier. Not only is next generation sequencing (NGS) getting cheaper, it is also more effective at pinpointing the exact genetic modification causing it.

Diploid specializes in rare disease diagnostics from NGS data, exploring two main types of genetic alteration: single nucleotide polymorphism (SNP) and copy number variation (CNV).

Fig 1: Genetic defects that can cause Rare Diseases: SNP and CNV

Taking opportunity of the added awareness of Rare Diseases Day, this Belgian Bioinformatics company is introducing a new business model for genomic diagnostics: pay only if you get results.

Diploid provides genome interpretation services to diagnose rare diseases in areas like intellectual disability, dysmorphisms, metabolic conditions.

This costs about €640 ($699) – or it’s free, if the resulting report cannot attribute the patient’s condition to any specific SNP or structural modification in the genome.

Taking into account that the price of sequencing a genome is now between €1100 and €1500, this could bring the price of a successful diagnosis to less than €2000 – a more cost-effective alternative (besides about 80x more sensitive), claims Diploid.

Diploid is not directly involved in the sequencing process (and so it stays away from NGS battles), but it is recommended by Genomics England, that is leading the 100,000 Genome Project – where Illumina is also involved.

Diploid’s diagnostic flowchart: the NGS data is analysed for SPNs, and matched with annotations and patient’s symptoms. After it, SNPs are filtered to get the most likely to cause the disease, and a report is written explaining the variants , and signed by a clinical geneticist. (Source: Diploid)

With the increasing amount of data from NGS, new Bioinformatics companies are quick to fill up the space created by the need to analyse it all.

A key aspect is to ease the transition of healthcare providers to Data-Driven Medicine – something that this pricing strategy from Diploid is probably trying to address.

It will be interesting to see if this business strategy, along with the focus in Rare Diseases, gives Diploid an edge in the genetic diagnostics market.

Feature image credit: © SSilver (BigStock ID65936881)

Fig 1 source: Autism Reading Room and Learn.Genetics

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