Out in Nature this week is a paper by three Genomes Unzipped authors reporting 71 new genetic associations with inflammatory bowel disease (IBD). This breaks the record for the largest number of associations for any common disease, and includes many new and interesting biological insights that you should all go and read about in the paper itself (pay-to-access I’m afraid) or on the Sanger Institute’s website.
One thing that we did not discuss in the paper was genetic prediction of IBD (i.e. using the risk variants we have discovered to predict who will or will not develop the disease). In this post I want to outline some of the situations in which we have considered using genetic risk prediction of IBD, and discuss whether any of them would actually work in practice.
Continue reading ‘Dozens of new IBD genes, but can they predict disease?’
Over at Nature News, Erika Check Hayden has a post about a recent Science Translational Medicine paper by Bert Vogelstein and colleages looking at the potential predictive power of genetics. The take-home message from the study (or at least the message that has been taken home by, e.g., this NYT article) is that DNA does not perfectly determine which disease or diseases you may get in the future. This take home message is true, and to me relatively obvious (in the same way that smoking doesn’t perfectly determine lung cancer, or body weight and dietary health doesn’t perfectly determine diabetes status).
A lot of researchers have had a pretty negative reaction to this paper (see Erika’s storify of the twitter coverage). There are lots of legitimate criticism (see Erika’s post for details), but to be honest I suspect that a lot of this is a mixture of indignation and sour grapes that this paper, a not particularly original or particularly well done attempt to answer a question that many other people have answered before, got so much press (including a feature in the NYT). A very large number of people have tried to quantify the potential predictive power of genetics for a number of years – why was there no news feature for me and Jeff, or David Clayton, or Naomi Wray and Peter Visccher, or any of the other large number of stat-gen folks who have been doing exactly these studies for years. ANGER RISING and so forth.
But of course, the reason is relatively obvious. Continue reading ‘Identical twins usually do not die from the same thing’
Dr Anna Middleton is an Ethics Researcher and Registered Genetic Counsellor, based at the Wellcome Trust Sanger Institute. She leads the ethics component of the Deciphering Developmental Disorders study, a collaborative project involving WTSI and the 23 National Health Service Regional Clinical Genetics Services in the UK. This project involves searching for the genetic cause of developmental disorders, using array-CGH, SNP genotyping and exome sequencing, in ~12,000 children in the UK who currently have no genetic diagnosis.
One of the issues raised by this, and many other research projects, is what should happen to ‘incidental’ findings, i.e. potentially interesting results from genomic analyses that are not directly related to the condition under study. Here Anna discusses the research she is conducting on this topic as part of the DDD study, and provides a link to the DDD Genomethics survey where you can share your own views (I should also disclose here that both Caroline and I also work on the DDD study).[KIM]
Whole genome studies have the ability to produce enormous volumes of valuable data for individuals who take part in research. However, as a consequence of analysing all 20,000+ genes, whole genome studies unavoidably involve the discovery of health related information that may have actual clinical significance for the research participant. Some of this will be considered a ‘pertinent finding’, i.e. directly related to the phenotype under study (e.g. the child’s developmental disorder); some of this will be considered an ‘incidental or secondary finding’ in that it is not directly linked to the phenotype under study or the research question that the genomic researchers are trying to answer.
Continue reading ‘Ethics and Genomic Research: ‘Genomethics’’
Razib Khan, more known for his detailed low-downs of population biology and history, has written an important post on Gene Expression, explaining in careful detail exactly how to run some simple population genetic analysis on public genomes, as well as on your own personal genomics data. The outcome of the tutorial is an ADMIXTURE plot (like the one to the left), showing what proportion of your genome comes from different ancestral populations. This sort of analysis is not difficult, but it can often be hard to know how to start, so Razib’s post gives a good landing point for people who want to dig deaper into their own genomes.
This tutorial also ties in to some political ideas that Razib has been talking about since the recent call to allow access to genomic information only via prescription. If you are worried about losing access to your genome, one option is to ensure that you do not require companies to generate and interpret your genome. As sequencing, genotyping and computing prices fall, DIY genetics becomes more and more plausible. Learn to discover things about your own genome, and no-one will be able to take that away from you. [LJ]
Continue reading ‘Analysing your own genome, bloggers respond to the FDA and more reporting on bogus GWAS results’
To celebrate 10 years since the back-to-back publications of complete human genomes in Science and Nature, Science has published series of articles looking back at the last 10 years of genomics, and forward to the future. The article contains short essays from Francis Collins and Craig Venter, the former talking about some of the successes of medical sequencing (including giving a name and photograph to the exome-sequenced IBD patient I discussed a few weeks ago), and the latter discussing how far we still have to go before genomics can reach its potential. Baylor’s Richard Gibbs talks about how the large-scale technical discipline of genomics and the biological subject of genetics are starting to re-merge, after the Human Genome Project saw the two diverging, and there is an oddly inspiring comment from theologian Ronald Cole-Turning about how genomics is redefining our vision of humanity.
Of particular interest is an article by Eliot Marshall on why genomics hasn’t yet had a large effect on medical practice, and what needs to be done to allow the genomic revolution to trickle into medical care. He argues that scientists and doctors need to meet each other half way; scientists need to focus more on showing the direct clinical utility of genomics, whereas doctors need to be more ready to accept new technologies and discoveries, and adapt the way they practice medicine to make full use of them. [LJ]
Continue reading ‘A decade of genomics, 60 new genomes, parenthood and sharing genetic data, and more on data return’
There is a real “wow” paper out in pre-print at the journal Genetics in Medicine. It is a wonderful example of the application of cutting edge sequencing technology to solve a medical mystery. Even better, the authors also include an auxiliary discussion about the medical and ethical issues surrounding the diagnosis, which raises some interesting issues about the transition from research to clinical sequencing.
A child manifested severe inflammation of the bowel at 15 months; antibiotics failed to clear it up, and he started to lose weight. Standard treatments seemed to have only sporadic effects, and only severe treatment with immunosuppressants, surgery and full bowel clearing could slow down the disease, which is not a long term solution. No cause could be found; the patient’s active immune system seemed to be acting abnormally, but all tests for the known congenital immune deficiencies came back negative. The doctors could try a full bone-marrow transplant, but without knowing what was causing the disease, and where it was localised, they had no way of knowing if such an extreme intervention would be successful.
Such a severe and early onset disease is likely to be genetic, but testing immune genes at random to find the mutation could take years before it turned anything up. Meanwhile, the child was seriously malnourished, and at times required daily wound care under general anaesthetic. A few years ago this might have been the end of the story.
Continue reading ‘Solving Medical Mysteries Using Sequencing’
The story behind this post is that my wife recently gave birth to our first son and we experienced a funny story about genetics the day following the birth. Before I start I should say, to reassure the reader, that I have no doubt that I am indeed the father of my child. But as you will see, a non-geneticist might have become worried when faced with the same situation.
Firstly, my wife has a negative rhesus type. This has important medical implications because if the baby were to have a positive rhesus type, she would create antibodies against this marker which could be life-threatening for any subsequent child of positive rhesus type. Basically this is a relatively big deal, but there are ways to deal with this, and therefore knowing the blood type of the baby is essential.
The day after the birth, while we are both lying on our bed, very tired, a midwife comes by and asks us whether we know the rhesus status of the baby. We answer negatively, she checks her notes and says, “Ah, good news, the baby is rhesus negative. The father must also be rhesus negative then!” Well, I am not…
Continue reading ‘Rhesus, paternity tests and 23andMe’
Welcome to the inaugural Friday links post. We’ll be using these posts to share interesting articles stumbled across by Unzipped members during the week.
We’re still tweaking the format, but the basic idea will be a brief paragraph of commentary followed by the initials of the person who wrote it.
Dan Koboldt reviews a recent paper reporting the use of whole-genome sequencing to find the mutation responsible for a severe genetic disease. Interestingly, in this case the disease was undiagnosed, and the causal variant was used to produce a diagnosis of sitosterolemia; more interestingly, this diagnosis had already been ruled out by another test, that was shown to be a false negative. [DM]
ScienceNews reports that researchers from the University of Copenhagen have got permission to sequence the genome of Sitting Bull, the native American war chief that led the battle of Little Bighorn. I don’t know exactly what they intend to learn from the genome scientifically, but it seems like this might serve primarily as a monument to a major figure in native American resistance. So the question I have is this: how can we go from a genome sequence (which is generally just a text file on a computer) to a public rememberance, something akin to the 1989 postage stamp shown to the left? [LJ]
Two papers in the current issue of Nature Genetics highlight recent inroads made in understanding the genetics of infectious disease susceptibility. The first found an association between risk of meningococcal disease and CFH, a gene previously implicated in age related macular degeneration. The second identified a susceptibility locus for tuberculosis in African samples. Paul de Bakker and Amalio Telenti have a nice News and Views piece about them as well, remarking on this welcome advance not only in understanding infection, but also in using GWAS to gain insight about disease risk in non-Europeans. [JCB]
Update: Dan Frost from the GoldenHelix blog has drawn our attention to a thought-provoking post on the future of GWAS studies. The post suggests that much of the missing heritability in complex disease is hiding in the set of variants that are badly tagged by existing chips, and proposes that GWAS studies in the future may include a sequencing phase to discover new variants in cases, followed by genotyping using custom genotype chips to capture this variation. The question, from my point of view, is how many common SNPs are there that aren’t well tagged by existing chips, and thus how much heritability could be hidden there? This is exactly the sort of question that the 1000 Genomes dataset was designed to answer. [LJ]
(This is an extended version of a short piece written as part of a series organized by the excellent Mary Carmichael at Newsweek. Readers eager for more detail on the statistics behind risk prediction should read Kate’s excellent discussion posted yesterday.)
In 2003 Francis Collins, having just led the human genome project to completion, made a prediction: within ten years, “predictive genetic tests will exist for many common conditions” and “each of us can learn of our individual risks for future illness”. The deadline of his prophecy is fast approaching, but how close are we to realizing his vision of being able to get a read-out of disease risk from a person’s DNA?
Continue reading ‘Why prediction is a risky business’