When it comes to predicting, diagnosing and treating Alzheimer disease (AD), interventions may be occurring as much as 20 years too late. And therapeutic solutions may lie not with one ultimate biomarker but with a combination of markers from imaging, genomic testing and/or blood and cerebrospinal fluid (CSF).
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Those were some of the conclusions of a panel discussion, “The New Role of Biomarkers and Big Data in Brain Health,” at Cleveland Clinic’s neuroscience-focused 13th Annual Medical Innovation Summit, held in late 2015.
Panel moderator James Leverenz, MD, Cleveland Director of the Cleveland Clinic Lou Ruvo Center for Brain Health, said the future of AD treatment hinges on pinpointing those critical biomarkers — with the help of big data.
“We have CSF, hippocampal volume and imaging for amyloid markers to help determine whether early pathology is taking place in the brain for diagnostic purposes, but we don’t have good biomarkers for disease progression or treatment response,” he said.
Dr. Leverenz’ questions to the panel, which included researchers and industry leaders, generated a compelling dialogue about AD and powerful take-home points. A few highlights are outlined below.
Jeff Hersh, MD, PhD, Chief Medical Officer of GE Healthcare, likened treating AD only after the patient had significantly compromised functionality to telling someone who is having a massive heart attack, “You shouldn’t eat so much junk food.”
The key to preventing and effectively treating AD and other neurodegenerative disorders, such as Parkinson disease, is to invert the current “ad hoc sick care system” to a preventive medicine system, said Brad Perkins, MD, MBA, Chief Medical Officer of Human Longevity, a genomics-based technology-driven company.
New tools and technologies could provide opportunities for much earlier interventions, well before symptoms even develop, Dr. Perkins said. “This is applicable not only to AD; it’s a pattern we’re going to see repeated across a number of neurologic diseases,” he predicted.
The “New Role of Biomarkers and Big Data in Brain Health” session panelists on stage at Cleveland Clinic’s 13th Annual Medical Innovation Summit.
“As we move more and more toward treatments that are disease-specific and disease-modifying, the value of imaging is going to rise exponentially,” Dr. Leverenz said.
If AD can be better characterized and staged through imaging (and other biomarkers), Dr. Hersh noted, pharmaceutical companies will be able to develop more effective symptomatic treatments and/or therapies to attack the underlying pathophysiology and thus delay or halt disease progression.
Hopes were once high that genetics would allow physicians and scientists to predict who was going to develop AD well before the disease emerged and also target treatments. “However, with the exception of a few rare mutations that are out there, that hasn’t happened,” said Jonathan Haines, PhD, Director of Computational Biology at Case Western Reserve University School of Medicine.
“The next thing we have to look at is modifications of the DNA sequence and what happens downstream, which is where some of these biomarkers come in — things you might find in biofluids and CSF,” Dr. Haines explained. “We need to mine that data in a way that allows us to figure out early in the process what’s going on, so we can identify people before they come to the clinic and say they’re having memory problems.”
In much the same way it has driven the evolution of cancer treatments, genetic testing will likely help predict patient response to the AD therapeutics of the future, which could set the stage for a greater emphasis on personalized medicine. “With Alzheimer disease, for example, we’re seeing some of the [apolipoprotein] E4 allele carriers responding differently to various therapeutics — and having different side effect profiles — compared with noncarriers,” Dr. Leverenz said.
Genomic testing is becoming more accessible due to better technology, increased efficiencies and lower costs, Dr. Perkins pointed out. “We have crossed a variety of important thresholds,” he said. “In the past 15 years, we’ve gone from needing $100 million and nine months for sequencing of a single genome to now being able to do a whole genome sequence for about $1,300 and at a much quicker pace.”
He added that the availability and cost of cloud-based computing power, the success of machine learning, and the transition to value-based care make genomics “the next frontier” in medicine. “We’re at the very beginning of the journey to translate the language of biology, in the form of sequence data, into the language of health and disease,” he said.
Getting to the bottom of some unanswered questions about AD will depend largely on the use of big data, said Vik Chandra, CEO of Muses Labs, a technology-based start-up focused on AD. “In addition to imaging and genomic data, there are thousands of types of blood tests — everything from standards to micromolecules — that can be applied today to help identify and correctly address the underlying causes of AD,” he said. “Probabilistic systems to make treatment practical are available today.”
An important part of the equation is to make big data small, panelists noted. “Machine-learning algorithms can’t be developed without doing that,” Dr. Perkins explained.
Gathering large amounts of data is crucial, but “then you need to process it and make sense of it,” Dr. Leverenz noted. “That’s where the future lies.”
A key step in moving AD interventions further upstream is to start enrolling patients much earlier in the disease process — perhaps even before they are symptomatic, Dr. Perkins said.
“If we can predict ahead of time who is at higher risk, we can make clinical trials more efficient and more cost effective while also speeding up the process,” Dr. Haines added.
Dr. Leverenz concluded that while there’s still much to learn from future research, “some of the signals seen with investigative therapies over the past year have been very encouraging. This could really be transformative.”
A full-length video of this and other 2015 Medical Innovation Summit sessions is available here.
