MIT’s Technology Review has an interesting blog post about Hugh Rienhoff, a clinical geneticist and entrepreneur, who is trying to apply personal genomics transcriptomics to find the causes of his daughter Beatrice’s unusual, Marfan’s syndrome-like symptoms. The blog post describes how Illumina (a leading company in DNA sequencing) has sequenced parts of the genomes of Rienhoff, his wife and his daughter, and how he has now spent about a year searching through these genome sequences for mutations that only Beatrice has.
In fact, looking at another blog post, it seems like they are actually sequencing RNA (mRNA, to be specific) rather than genomic DNA. This makes a lot of sense, because RNA sequencing (RNA-seq) gives information about genes that are actually being expressed – transcribed into mRNA and then presumably translated to proteins. This sort of “transcriptome profiling” should potentially be able to give a lot of information about disease states beyond what can be gleaned from a genome scan (although those are, of course, informative as well.)
From the sequencing data, Rienhoff has compiled a list of about 80 genes that are “less active” in Beatrice than in her parents. (I wonder what tissues or cell types they assayed?) According to the Nature blog post, Illumina will be doing similar transcriptome profiling on up to nine family trios (mum, dad, child) where the child has, for instance, autism or Loyes Dietz syndrome.
A quote from the Technology Review blog post:
One of the biggest challenges, Rienhoff says, is the software available to analyze the data. “To ask the questions I want to ask would take an army,” he says. “I’m trying to connect the dots between being a genomicist and a clinical geneticist. I don’t think anyone here realizes how difficult that is. I’m willing to take it on because it matters to me.”
Reading about this sort of literally personal genomics/medicine made me think of Jay Tenenbaum and his company CollabRx, which offers a “Personalized Oncology Research Program”, where they “…use state-of-the-art molecular and computational methods to profile the tumor and to identify potential treatments among thousands of approved and investigational drugs” So the approach here is presumably also to do some sort of individual-based transcriptional profiling, but this time on tumor material. After all, cancer is a heterogeneous disease (or a heterogeneous set of diseases) and tumors probably vary widely between patients. Echoing Rienhoff above, Tenenbaum said in an interesting interview a couple of months ago that biology is becoming an information science and that CollabRx are “heavily dependent on systems and computational biology” (=software, algorithms, data analysis, computing infrastructure).
I applaud the effforts of CollabRx, while simultaneously being sceptical about what can be achieved today using this approach in the way of clinical outcomes. But someone has to be the visionary and pave the way.