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The challenges of NGS technologies

In this article, you will learn about some of the challenges associated with high-throughput DNA sequencing.
© St George’s, University of London

Genomic technologies have the potential to transform the way that we practice medicine, and ever faster, cheaper DNA sequencing offers increasing opportunities to prevent, diagnose and treat disease.

However, genomic technologies are not without their challenges.

Genomic technologies and their challenges

It is essential that, if genomic technologies are to be successfully integrated throughout medicine, we consider each of these challenges and how they might be addressed.

  • How can we store the huge datasets generated?
  • How do we handle such large datasets?
  • How do we clinically manage variants of uncertain significance?
  • What do we do when we identify an incidental finding not relevant to the condition being investigated?
  • How do we identify the clinically relevant variant amongst the millions of variants?
  • How do we deal with the complex ethical issues associated with genomic technologies?

Storing big data

For instance, storing big data is a huge challenge for which the NHS needs to be prepared with investment in bigger computers with greater memories.

Whilst the A C T G of our genomic code could be stored on the memory of an iPhone, the amount of data needed to generate each individual’s genome is an order of magnitude greater.

The computing power

This is exemplified by the computing power predicted to be required for the 100 000 Genomes Project which is likely to reach several petabytes (where one petabyte is a million gigabytes of data). Imagine, therefore, the computing power required if genomes were regularly being analysed and stored as part of normal clinical care.

Even if we are able to successfully store and handle these huge datasets, we then need to be able to sift through the millions of normal variants to identify the single (or, rarely, several) pathogenic, disease-causing mutation.

The proverbial needle in a haystack

This is akin to searching for the proverbial needle in a haystack and presents one of the greatest challenges of the new technologies. Whilst this can, to an extent, be achieved through the application of complex algorithms, these take time and considerable expertise to develop and are not infallible.

In addition, even after these data have been sifted by the bioinformaticians, it is highly likely that clinicians will be left with some variants where there is insufficient data to enable their definitive categorisation as either pathogenic or non-pathogenic.

Unknown variants

This may be because we simply do not know enough about the gene because the particular variant has not previously been reported and/or it is identified in an unaffected parent. These variants must be interpreted with caution and, more usually, their interpretation will require input by a genetics expert in the context of the clinical presentation where an “innocent until proven guilty” approach is often adopted.

Incidental findings

Finally, if we are to interrogate the entire genome or even the exome, it is foreseeable that we will routinely identify ‘incidental’ or secondary findings – in other words, findings not related to the initial diagnostic question. The UK has so far advocated a conservative approach to incidental findings.

While genome sequencing generates data about the whole genome, it is possible to analyse only subsets of these data.

In the clinical diagnostic scenario, it has been suggested that it is reasonable only to analyse the data relating to the genes that are pertinent to the clinical situation: in other words, in a child with developmental delay, detailed analysis should be restricted to those genes known to be associated with this phenotype.

In this way, information relating to unrelated genes, such as BRCA1, that may complicate the interpretation is avoided.1

Given the challenges inherent to the use of new genomic technologies, it is essential that clinicians consider how the integration of genomic technologies into medicine will impact their clinical practice; not only the diagnosis and treatment of disease but also what should be discussed with patients prior to genetic testing when obtaining consent and when a genomic result is communicated back to the patient and/or their family.

Talking point

If, like most of us in the NHS, you will be using genomic data in your clinical practice or even if, as a patient, you find these issues of particular interest we would love to hear from you in the comments.

For instance, what would you feel about being told you were at risk of developing a genetic condition unrelated to the question or concerns that brought you to the Doctor in the first place?

Do you think we all have a right to our genomic data or should Clinicians act as “gatekeepers” informing us only of the results pertinent to the clinical question?

We shall be considering these issues in more depth later in the course, along with some of the ethical issues surrounding incidental findings, so you may wish to revisit some of your ideas later on as well.

Do you want to know more?

If you would like to know more about the challenges associated with genomic technologies, please take time to look at “Policy challenges of clinical genome sequencing” by Caroline Wright and colleagues in the BMJ.

1 Wright, Caroline, et al. “Policy challenges of clinical genome sequencing.” BMJ 347 (2013)

© St George’s, University of London
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