Could degenerative diseases be treated by changing the brain?
As global populations age, neurodegenerative diseases will continue to present public health challenges. Neurological disorders already affect hundreds of millions of people worldwide, and the number of people with dementia is projected to quadruple by 2050, reaching 115m, according to the World Health Organization.
A few months ago at the Massachusetts Institute of Technology’s EmTech2014 conference, Dr Pamela Sklar, a Mount Sinai Hospital geneticist, neuroscientist and clinical psychiatrist, revealed an emerging new take on neuropsychiatric conditions.
There’s now “profound molecular evidence”, she said, that conditions from schizophrenia to bipolar disorder to Parkinson’s are not, as long thought, the results of single genetic dysfunctions, but rather are “extremely polygenic”—ie the result of many genetic variations. This dovetails with the increasingly accepted view in the scientific community that such conditions also are expressed by neural network dysfunctions.
This multi-actor, network-based view appears especially relevant to and with Parkinson’s disease, where cell death in the basal ganglia interrupts signalling throughout the brain’s motor-control network. Deep brain stimulation (DBS) seems to smooth that network’s communication pathway via an implanted device that transmits high-frequency electrical pulses into the brain. Such smoothing of the motor-control network’s communication pathway has been used to provide temporary, immediate relief of tremors and other symptoms of Parkinson’s disease.
Sending signals only addresses half of the conversation with the neural network, however. In October 2013, a team of Stanford surgeons upped the ante, implanting a device (made by Medtronic) capable not only of sending pulses, but of reading neural signals generated by that stimulating current. (Such feedback generally only is possible during brain surgery.)
Amassing and interpreting neural readings might elucidate precisely how neural networks go awry in different diseases, as well as how DBS affects various neural networks. The hope is that, eventually, bespoke devices will use patient biofeedback to improve treatment efficacy.
Initial beneficiaries of such technology might not be those with Parkinson’s disease, however, but those with a less-complicated condition—epilepsy. While both conditions involve interruptions of normal brain activity, epilepsy is less complex than Parkinson’s as its hallmark is not a continuum of dysfunctions but rather distinct, finite episodes of circuit disruptions.
Here, too, the idea of biofeedback is shaping emerging treatments. Closed-loop, implantable neurostimulators (such as once made by NeuroPace in California) are now being designed to observe neural activity and immediately respond to any seizure-inducing abnormalities with preventive pulses.
A less-invasive offshoot of DBS is transcranial direct-current stimulation (tDCS), which would eschew a permanent implant in favour of, say, an electrode-laden cap. Such devices are part of the emerging field of bioelectric medicine. GlaxoSmithKline, for example, recently established a $50m fund to support this field of research. Researchers claim that electrical stimulation in the form of either wearables or implantables, if harnessed correctly, could potentially rival chemical treatments for issues such as mild depression, migraine management, and even brain injury.
Promising as they are, such treatments are not yet refined enough to “elucidate exactly which cells drive what behaviours,” writes Dr Edward Boyden in a recent issue of Scientific American. He points out that a single cubic millimetre of brain tissue contains approximately 100,000 neurons and a billion synaptic connections.
Electric pulses might thus be considered a form of fire-hose treatment, one that could benefit from optogenetics, a field he helped originate and that refines the idea of neural stimulation by outfitting neurons with light-sensitive molecules. Light therapy excites only those cells, thus allowing “more precise manipulation of brain circuits”. Such specificity could help refine targeting for both pharmaceuticals and electrical stimulators.
Also exploring the circuitry pathway is Stanford researcher Dr Michelle Monje, the senior author of a 2014 paper that turns the spotlight on myelin, the sheathing cells that insulate neural fibres and make up the “roads, highways and freeways that connect one place to another” in the brain.
Myelin insulation forms the basis of part of the brain’s “plasticity”, which is the flexibility that allows us to learn and adapt. Even small modifications to the structure or thickness of the sheath can impair the speed of neural-impulse conduction.
If, as her study suggests, neuron activity causes changes in myelin, then learning how to optimise both could improve conduction and communication. That, in turn, could lead to therapeutic strategies for disorders, including multiple sclerosis, that degrade myelin and thus impair nerve transmission.
Other areas yielding advances and new knowledge include genome editing and stem-cell therapy. But for some psychiatric disorders such as schizophrenia or autism, the biggest insights have less to do with new technologies and more with amassing and analysing big data.
In the past, scientists focused on homing in on the differences between conditions, remaining wary of medications that worked for more than one disorder. Today, Dr Sklar said, researchers are beginning to embrace the connections among such diseases, potentially leading to “more efficacious pathways”.
In the future, combining integrated genetic and epigenetic big data with stem cell-based tissue analysis—analysing live brain tissue generally is not possible—could lead to further insights. Dr Sklar’s “pie in the sky” ideal would be that doctors someday screen tissue before even choosing a particular therapy or medication for a patient.
Whatever treatments emerge from these new insights, they won’t be here tomorrow. As Dr Steven Hyman of the Broad Institute pointed out at EmTech2014, although such therapies provide a “glimmer of light”, it takes about 10-15 years for a drug to go from concept to market.
This article is published in collaboration with GE Look ahead. Publication does not imply endorsement of views by the World Economic Forum.
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Author: Holly Hickman writes for GE Look ahead.
Image: Brain cells shown on a scan. REUTERS.
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