Paul Allen’s Big Bet to ‘Uncover the Essence of What Makes Us Human’

3/22/12Follow @xconomy

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look deeper than the cellular level, down to the molecular level of the brain. This will be based on using high-speed/low-cost gene sequencing machines to spot DNA mutations that affect brain development and can lead to disease. The other key technology in this initiative will be the use of what scientists call “induced pluripotent stem cells” in which adult skin or blood cells are essentially re-programmed into a stem-cell like state so that they can become any type of cell in the body—including many types of neurons. By looking at DNA mutations, and then seeing how that DNA manifests itself in actual neurons from people, the scientists hope to be able to predict how brains will function. “Our ultimate goal is to generate a set of molecular tools that will empower the scientific community” to develop better understanding of how aberrant genes affect behavior and various diseases, Koch said.

There will obviously be big challenges in pulling off this kind of work, aside from the sheer technical difficulty. Jones, the institute’s CEO, said his 185 employees are spread among three buildings in Fremont, and it would be better for collaboration to be clustered under one roof (he hinted that he’s working on that one). For Koch, there’s a sociological challenge in recruiting bright scientific minds. Since top scientists tend to be independent sorts who work in narrow disciplines, and tend to follow their own latest ideas. The culture is about keeping ideas and data secret until blockbuster results get published in a peer-reviewed journal. That’s the opposite of an open-source effort, in which each individual can’t just follow whatever idea strikes them, and keep all the data and glory for themselves. “This is a team effort,” Koch says. “We have to attract the world’s best talent, and then instill in them a team spirit that we all have to work together, for common goals, common methods.”

More than once, Allen talked about the complexity involved in the work, and how daunting it is. When Koch tried to sum up what this effort is about, it’s not the kind of thing you can very easily put in a single sentence.

“We have a unique opportunity to truly push the field forward,” Koch said. “This is a large-scale, industrial-size effort to synthesize all of our genomic, anatomical, physiological, computational, and theoretical knowledge into a comprehensive picture of how the most complex piece of organized matter, the brain, develops and functions to produce perception, memory, and consciousness.”

Allen Institute for Brain Science leaders. From left, chief scientific officer Cristof Koch, founder Paul Allen, CEO Allan Jones

If you’re like me, you probably had to read that sentence more than once. It’s a big undertaking, and all the answers neuroscientists want won’t magically appear at the end of four years. Koch acknowledged that it’s likely to turn out like cosmology—once scientists learn a bit more about the universe, they realize there’s a lot more there to explore than previously thought.

But for Allen, a guy who grew up on science fiction, this is partly about exploration of new frontiers, and partly about a desire to make an impact on humanity and health.

“I’ve always been fascinated by the brain,” Allen said. “I started out as a programmer in high school, and the brain works in a completely different and unknown fashion than the way computers do. There is no greater challenge, with potentially huge impact, than understanding how brains work. For me, it’s fascinating. And as someone who’s been touched by neurodegenerative diseases—my mother has Alzheimer’s, for example—I want to see cures brought forward.”

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  • http://www.xconomy.com/author/ltimmerman/ Luke Timmerman

    Eric Schadt, the director of Mt. Sinai School of Medicine’s Institute for Genomics and Multiscale Biology, offered a long, detailed and technical response when I asked him for comment on on the new Allen Institute initiatives. Readers should note that Schadt is quite familiar with what’s going on, as he is an advisor to the Allen Institute. Here’s what he had to say:

    Eric Schadt: “I think this is a really big deal. Diseases such as autism and schizophrenia are very complex, involving a strong genetic variance component but also environmental component. The genetic variance component is very complex though, with a predicted 500-1000 genetic loci, for example, underlying the genetic variance component of autism. Further, because these diseases involve some form of neurological dysfunction, one cannot study it at the molecular level as easy as cancer where tumor biopsies are readily available or diseases of peripheral organs in which again biopsies are more readily doable.

    One of the revolutions of the last decade has been reprogramming of cells like fibroblasts and then reprogramming them into pluripotent stem cells and then differentiating those into cell types or tissues that are relevant to the study of disease. Whether differentiating stem cells into adipocytes and beta cells to study molecular and cellular phenotypes associated with diabetes or neurons to study diseases like schizophrenia and Alzheimer’s, iPSCs generated from patients with these diseases offers a novel and exciting way to elucidate the complexity of complex human diseases. The naturally occurring genetic variation that exists within patient populations that underlie diseases like autism perturb molecular networks that underlie the pathophysiology of the disease. Therefore the isolation of cells from patients that harbor those genetic perturbations and reprogramming and differentiating those cells into disease relevant contexts, provides the opportunity to directly characterize the molecular and cellular changes that lead to pathophysiological states.

    This type of resource will be incredibly valuable to the scientific community at large because it will enable construction of the molecular networks of disease, thereby enabling an understanding of mechanisms, provide the appropriate reagents (disease relevant cell types) for drug screening, enable detection of disease biomarkers and drug response biomarkers and so on. So big enabling potential here.

    This goes well beyond what could be done in a PI driven environment because this is big science. Running at the scale of hundreds of patients and controls to isolate fibroblasts or other cell types that can be reprogrammed to iPSCs, carrying out the reprogramming, the differentiation in a reproducible way, generating all of the omics and cellular phenotype data off of that, involves a number of technical challenges that require big technology to solve, focused teams with expertises in many different areas (from robotics, to molecular biology, to informatics and computation biology), and of course considering resources (money). In addition, targeting specific genes or constellations of genes in cells to validate findings, perturb networks in relevant ways, etc., in ways that allow modulation of the gene’s activity in different contexts, again has many technical challenges in running at scale (so beyond handfuls of genes that might classically be studied in an individual lab).

    Okay, Luke, sorry to drag on, but I think this is a truly exciting project that can help transform our understanding of some of the most difficult, but prevalent, neuropsychiatric diseases, and they have recruited Ricardo [Dolmetsch], one of the more capable researchers on the planet in this area to lead this effort with the expert team assembled and growing at the Allen Institute.”

  • Lance Stewart

    Luke thank you for covering this important story.

    Collectively, we suffer from a lack of coordination and sharing of neuroinformatics data that could contribute to the greatest healthcare improvements of our lifetime. Paul G. Allen’s gift to promote open neuroscience is truly remarkable.

    There is tremendous opportunity to harness the combined investments of industry, academia, government, and patient advocacy in a focused game-changing approach to neuroscience.

    My hope is that over the next 10 years we will see a social networked approach to discovery of new preventions, diagnoses, and treatments for brain disease. Specifically, I can see a day when Pharma/biotech companies donate their chemical and device resources to academic/gov/research institution labs for full interrogation of potential utility in an open science mode of shared data. In turn, the new insights will provide enough data for smart computer systems to help guide the engineering of a new intellectual property that enables a paradigm shift in neuro-medicine. The stakes are too high for this not to happen.