Tag Archive for 'genomic medicine'

Dozens of new IBD genes, but can they predict disease?

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.

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Genome interpretation costs will not spiral out of control

Mo' genomes, mo' money?

An article in Genetic Engineering & Biotechnology News argues that as the cost of genome sequencing decreases, the cost of analysing the resulting data will balloon to extraordinary levels. Here is the crux of the argument:

We predict that in the future a large sum of money will be invested in recruiting highly trained and skilled personnel for data handling and downstream analysis. Various physicians, bioinformaticians, biologists, statisticians, geneticists, and scientific researchers will be required for genomic interpretation due to the ever increasing data.

Hence, for cost estimation, it is assumed that at least one bioinformatician (at $75,000), physician (at $110,000), biologist ($72,000), statistician ($70,000), geneticist ($90,000), and a technician ($30,000) will be required for interpretation of one genome. The number of technicians required in the future will decrease as processes are predicted to be automated. Also the bioinformatics software costs will plummet due to the decrease in computing costs as per Moore’s law.

Thus, the cost in 2011 for data handling and downstream processing is $285,000 per genome as compared to $517,000 per genome in 2017. These costs are calculated by tallying salaries of each person involved as well as the software costs.

These numbers would be seriously bad news for the future of genomic medicine, if they were even remotely connected with reality. Fortunately this is not the case. In fact this article (and other alarmist pieces on the “$1000 genome, $1M interpretation” theme) wildly overstate the economic challenges of genomic interpretation.

Since this meme appears to be growing in popularity, it’s worth pointing out why genome analysis costs will go down rather than up over time:
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Ethics and Genomic Research: ‘Genomethics’

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.

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Ulcerative colitis genetics, Nature on the human genome

Yes, it’s Friday Links time yet again here at Genomes Unzipped.

A paper in Nature Genetics this week reports the results of a large meta-analysis of GWAS studies into ulcerative colitis, which more than doubles the number of loci known for the disease from 18 to 47. This pushes the proportion of heritability explained from 11 to 16%, and sheds more light on the shared and non-shared pathways between ulcerative colitis and Crohn’s disease, along with the interplay with other immune and inflammatory disorders.

The lead author is a Genomes Unzipped contributor, but he emphatically refused to contribute to this Friday Links post, on the grounds that he doesn’t want to blow his own trumpet. So, instead, here is a quote from the Sanger Institute’s press release:

“The genomic regions we have identified give us an insight into the biology underlying ulcerative colitis,” says Dr Carl Anderson, from the Wellcome Trust Sanger Institute and first author on the paper. “These important initial discoveries are the building blocks on which we can begin to derive better IBD treatments, though much further work is needed before these become a clinical reality.” [LJ]

Nature has a special issue this week devoted to the decade of progress since the publication of the human genome sequence. Eric Lander, who was first author on the original Human Genome Project paper, has a long and thoughtful commentary on the subsequent impact of that publication across a wide range of fields. Elaine Mardis accompanies Lander’s piece with a discussion of the astonishing advances in sequencing technology over the last decade (including a figure that emphasises the tremendous impact of the development of the Solexa/Illumina Genome Analyzer platform, which boosted sequencing capacity by eight orders of magnitude in a single year!).

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