Human disease genetics has undergone a major revolution. The Human Genome Project was completed in 2003 – this took $US10 billion and over 13 years to generate a near complete sequence of the human genome.
Now, thanks to huge advances in massively-parallel sequencing technology, we can sequence a human genome in under a day, for $US1000, and so understanding how genetic alterations can affect human development and health has become a data-crunching problem!
The impact on genetic disorders has been unprecedented, with particular impact on rare disorders. In the past, new disease genes were predominantly found by studying large families using genetic analysis tools, or large groups of patients using a candidate-informed approach, but now it only can take one family to uncover a whole new area of biology and health.
In the US, this technology is now being pioneered in neonatal intensive care units to diagnose and potentially inform treatment for critically ill babies. In Australia they are trialling carrier testing for prospective parent couples, to inform on risks of more ‘common’ rare disorders prior to, or early in pregnancy. It is certainly an exciting period to be able to contribute to such research in both New Zealand and globally.
So how do we data-crunch to arrive at “the answer” for a patient? We have several approaches we can utilise to filter out genetic alterations we don’t think are likely to be pathogenic. This is particularly powerful for disorders that are rare and highly penetrant, such as my research focus - single-gene disorders. These are also known as Mendelian disorders, named after the Austrian monk Gregor Mendel, whose research on peas formed the foundational rules of genetic inheritance.
The first and most effective step we use is to take advantage of the rarity inherent with rare disorders and apply assumptions about how common a genetic alteration would be that could cause such a condition. For example, for a condition affecting less than 1 in 1,000,000 people, we wouldn’t expect to see such an alteration present in 50% of the population and in fact, we can use a very low frequency threshold (0.5%), that allows us to de-prioritise the vast majority of alterations we would detect in our genetic analysis. There are now large global datasets freely available that we can extract such information from to assist this filtering approach. These large datasets are very European-centric, and we know different ethnicities demonstrate variation in frequencies of different genetic variants. In the New Zealand context, this means we need to be especially cautious during our analysis of Māori families.
We then combine this filtering step with further steps based on the inheritance model we choose to test, such as whether the parents have passed a variant on or it has appeared new in the patient (de novo), as well as some assumptions about the consequence on the gene. Our goal is that after this data-crunching we will have a small list of variants to further assess. We then consider the clinical features of the patient and the available medical and biological literature to give us clues as to which variants to prioritise for further analysis.
Occasionally, there is an adrenaline spike as the list reveals a strong candidate in a potential new disease gene! One exciting example of this is a New Zealand child we have been studying who has extreme microcephaly and intellectual disability, in which we identified a de novo variant altering an essential protein whose function is conserved in yeast. Through our clinical networks and a genetics matchmaking website, we now have five patients from around the world (NZ, Japan, Malaysia, Belgium, UK) whom all share the exact same de novo variant, with the same set of clinical features – a striking find indeed! This provides excellent genetic evidence that such a variant, which has not been observed in any healthy person, underlies the dramatic consequences on brain development we observe in this patient cohort. We are now turning to molecular biology to gain cell-based evidence confirming this variant is deleterious to normal protein functioning.
A more poignant example is a New Zealand girl with short stature and intellectual disability where we identified a genetic defect in glycosylation. While the diagnosis is an established syndrome (albeit in less than 15 patients published worldwide), this girl was clinically atypical and didn’t have the tell-tale signs. Oral supplementation is available, and we are hoping this could prevent further damage to her brain and development.
Genetic sequencing has undergone a revolution in recent times and as technology and techniques continues to advance, so too does our understanding. My, and others, research teams are proud to help New Zealand families, either through identifying a genetic variant underlying a known syndrome, or discovering a new syndrome altogether – although as often happens in research, more findings leads to more questions!