Archive for the 'Opinion' Category

Last week, the FDA sent a sternly-worded letter to the personal genomics company 23andMe, arguing that the company is marketing an unapproved diagnostic device. Many have weighed in on this, but I’d like to highlight a thoughtful post by Mike Eisen.

Eisen makes the important point that interpreting the genetics literature is complicated, and a company (like 23andMe) that provides this interpretation as a service could potentially add value. I’d like to add a simple point: this is absolutely not limited to genetics. In fact, there are already many software applications that calculate your risk for various diseases based on standard (i.e. non-genetic) epidemiology. For example, here’s a (NIH-based) site for calculating your risk of having a heart attack:

And here’s a site for calculating your risk of having a stroke in the next 10 years:

And here’s one for diabetes. And colorectal cancer. And breast cancer. And melanoma. And Parkinson’s.

I don’t point this out because it leads to an obvious conclusion; it doesn’t. But all of the scientific points made about risk prediction from 23andMe (the models are not very predictive, they’re missing a lot of important variables, there are likely errors in measurements, etc.) of course apply to traditional epidemiology as well. Ultimately, I think a lot rides on the question: what is the aspect of 23andMe that sets them apart from these websites and makes them more suspect? Is it because they focus on genetic risk factors rather than “traditional” risk factors (though note several of these sites ask about family history, which of course implicitly includes genetic information)? Is it the fact that they’re a for-profit company selling a product? Is it something about the way risks are reported, or the fact that risks for many diseases are presented on a single site? Is it because some genetic risk factors (like BRCA1) have strong effects, while standard epidemiological risk factors are usually of small effect? Or is it something else?

By now, we’re probably all  familiar with Niels Bohr’s famous quote that “prediction is very difficult, especially about the future”. Although Bohr’s experience was largely in quantum physics, the same problem is true in human genetics. Despite a plethora of genetic variants associated with disease – with frequencies ranging from ultra-rare to commonplace, and effects ranging from protective to catastrophic – variants where we can accurately predict the severity, onset and clinical implications are still few and far between. Phenotypic heterogeneity is the norm even for many rare Mendelian variants, and despite the heritable nature of many common diseases, genomic prediction is rarely good enough to be clinically useful.

The breadth of genomic complexity was really brought home to me a few weeks ago while listening to a range of fascinating talks at the Genomic Disorders 2013 conference. Set against a policy backdrop that includes the recent ACMG guidelines recommending opportunistic screening of 57 genes, and ongoing rumblings in the UK about the 100,000 NHS genomes, the lack of predictability in genomic medicine is rather sobering. For certain genes and diseases, we can or will be able to make accurate and clinically useful predictions; but for many, we can’t and won’t. So what’s the problem? In short, context matters – genomic, environmental and phenotypic. Here are six reasons why genomic prediction is hard, all of which were covered by one or more speakers at Genomic Disorders (I recommend reading to the end – the last one on the list is rather surprising!):

Continue reading ‘Why predicting the phenotypic effect of mutations is hard’

The recent announcement that the UK Government has earmarked £100 million to “sequence 100,000 whole genomes of NHS patients at diagnostic quality over the next three to five years” raises a number of questions, with which the Department of Health are no doubt grappling as I write. I’ve previously discussed the thorny issue of using targeted versus whole genome sequencing to maximize diagnostic yield and benefit patients. However, one of the great achievements of next generation sequencing technologies is to make the assay – actually sequencing genome (or some portion of it) – one of the easier parts of clinical genomics. Although laboratories will have to be suitably equipped, staffed and flexibly managed to deal with high sample throughput and ever changing scientific specifications, the biggest challenge will be to implement genomic knowledge in the clinic.

Continue reading ‘£100M for whole patient genomes – an implementation challenge’

About a year ago on this site, I discussed a model for addressing some of the major problems in scientific publishing. The main idea was simple: replace the current system of pre-publication peer review with one in which all research is immediately published and only afterwards sorted according to quality and community interest. This post generated a lot of discussion; in conversations since, however, I’ve learned that almost anyone who has thought seriously about the role of the internet in scientific communication has had similar ideas.

The question, then, is not whether dramatic improvements in the system of scientfic publication are possible, but rather how to implement them. There is now a growing trickle of papers posted to pre-print servers ahead of formal publication. I am hopeful that this is bringing us close to dispensing with one of the major obstacles in the path towards a modern system of scientific communication: the lack of rapid and wide distribution of results.*
Continue reading ‘The first steps towards a modern system of scientific publication’