Big Data Was the Big Theme at Shortened NIH Summit

10 Mar 2018

Scientists gathered on March 1 in Bethesda, Maryland, for the 2018 NIH Alzheimer’s Disease Research Summit, ready to absorb the 82 presentations scheduled over two days. Then a nor’easter forced closure of U.S. government buildings and put the kibosh on Day 2. Even so, researchers seemed impressed by the summit. Scientists interacted across disciplines with colleagues whom they might not otherwise meet, and the NIH took away 75 pages of funding recommendations for future research. “There were a lot of interesting ideas, from basic science to clinical studies,” said Marco Colonna, Washington University, St. Louis. “It was a bit overwhelming, but extremely valuable.”

This was the third AD research summit hosted by the NIH, as mandated by the National Alzheimer’s Project Act. Recommendations from the first two summits in 2012 and 2015 helped shape the NIA-funded research agenda. With the NIH budget for AD and related disorders almost tripling to $1.414 billion in the last three years, the third summit has the potential to make a major impact on the field. As NIH Director Francis Collins emphasized in his opening address, this is a critical time in Alzheimer’s research. “Any notion that a quick path to prevention or treatment was going to emerge from 2012 … has turned out to be naïve,” Collins said. But he noted that the field knows more than in 2012 and urged leaders to bring boldness, audacious optimism, and a readiness to consider dramatic new approaches to the problem.

The first day of the summit outlined some of those approaches. Organized by Suzana Petanceska and Laurie Ryan of the National Institute on Aging, the summit was to cover seven themes:

Novel Mechanistic Insights into the Complex Biology and Heterogeneity of AD
Enabling Precision Medicine for AD
Translational Tools and Infrastructure for Predictive Drug Development
Emerging Therapeutics
Understanding the Impact of the Environment to Advance Disease Prevention
Advances in Disease Monitoring, Assessment, and Care
Building an Open Science Research Ecosystem to Accelerate AD Therapy Development.

Theme sessions featured three to four 15-minute talks followed by five-minute, one-slide summaries of related topics by up to nine selected panelists, leaving little time for Q&A or debate. The cancelled second day will be rescheduled soon, NIH staff said.

Big data and precision medicine dominated the day, building on plenary talks by Eric Schadt from the Icahn School of Medicine at Mount Sinai, Los Angeles, and Joni Rutter of the NIH. Rutter gave an update on the All of Us research program, formerly called the Precision Medicine Initiative cohort. It plans to gather data on 1 million Americans as a foundation to enable precision medicine, or medical treatment and care tailored to individual patients. So far, 16,500 participants have enrolled. They have provided medical histories and agreed to share medical records and give blood, urine, and saliva for future analysis. The program hopes to eventually incorporate behavior and lifestyle data, including information from wearable devices.

Schadt thinks the possibilities from mining such data are staggering. He emphasized that a broad array of upcoming technologies will generate vast amounts of information. Data from next-generation sequencing, electronic medical records, wearables, geocoding that catalogs a person’s “exposome,” i.e., exposure to environmental hazards such as air pollution or even getting stuck in traffic, and other sources will add up to yottabytes, Schadt said. For the mathematically minded, that is 10²⁴ bytes, or 10 trillion gigabytes, enough to store 2,000 trillion songs on your smartphone. The challenge, said Schadt, is analyzing the data.

Enter machine learning. Algorithms can be trained to identify, in unbiased fashion, characteristics that distinguish healthy controls from people with disease. Schadt showed how such in silico crunching of data from the AMP-AD knowledge portal uncovered VEGF as a master regulator gene downregulated in AD. Overexpressing this gene in 5xFAD mice dramatically reduced Aβ pathology, said Schadt.

Joel Dudley, fromMount Sinai in New York, told the audience that, to his great surprise, machine learning picked up a greater abundance of viral RNA and DNA in various brain regions of AD patients. Dudley was mining open data from the AMP-AD portal for network states that distinguish normal controls from early and late AD, with a view to drug targeting. “As we looked at network transitions, we kept getting screaming signals for viral biology,” he said. Specifically, he found that herpes viruses 6 and 7, as well as herpes simplex viruses, are amplified in Alzheimer’s. The findings recapitulated across multiple datasets including those from Mount Sinai, Rush’s Religious Orders Study and Memory and Aging Project, and from the Mayo Clinic sample. Taking it a step further, Dudley found that the abundance of viruses correlated with clinical and neuropathological traits of AD, such as the CDR, plaque load, and Braak staging.

Looking for quantitative trait loci that change with viral load (vQTLs), HHV6/7 and HSV vQTLs correlated with AD traits. With these vQTLs, Dudley built viral-host molecular networks in an effort to take the data beyond correlations and look for causality. This turned up vQTLs that elicited changes in the host, and vice versa. These networks were enriched in genetic loci that had turned up in previous AD genome-wide association studies.

Dudley is not sure what this data means. He told Alzforum that others at the summit have similar findings. He does not think viruses cause AD. Rather, because they integrate into the host genome, they may become activated when neurons come under stress, as during disease. Then they may start to co-opt the cell’s transcriptional machinery for viral reproduction, tipping the whole system toward a more pathological state. “This type of work highlights the benefit and complexity of a data-driven approach,” said Dudley, who believes big data has the power to shake up the field. “Studying AD necessitates a systems view of how information flows from the immune system to neurons to metabolism and back. By understanding these relationships, we hope we can put together a much larger picture of the disease that will reveal non-traditional [drug] targets,” he said.

Other massive datasets are coming online that will help in that analysis. Matthias Arnold from the Helmholtz Center Munich, Nick Seyfried from Emory University, Atlanta, Rachel Whitmer at the University of California, San Francisco, and Cornelia van Duijn from Erasmus University Medical Center, Rotterdam, the Netherlands, showed, respectively, how metabolomics, proteomics, epidemiology, and genetics can be woven into a big data fabric.

Other speakers presented tools and techniques that expand our understanding of the brain. Sean Bendall from Stanford University co-leads MIRIAD, a.k.a. multiplexed imaging of resilience in Alzheimer’s disease. Bendall and colleagues use a technique called multiplexed ion beam imaging (MIBI) to simultaneously measure expression of up to 40 molecules at a time in a tissue section. MIBI uses antibodies labelled not with fluorescent dyes but with specific isotopes that are liberated by the ion beam and measured by mass spectrometry. The technique can resolve down to the level of individual synapses. Bendall uses MIBI to search for expression patterns that emerge more in people who are resilient or prone to AD, again using machine learning to tease different patterns out from vast amounts of data.

Other panelists emphasized how epidemiology, genetics, and comorbidities affect resilience. Ben Readhead from Arizona State University, Phoenix, described a single-cell RNAseq atlas of brain transcription. It could catalog the degree of transcriptomic heterogeneity in the brain, uncover new subtypes of cells, and identify shifts in gene expression that occur in the face of emerging pathology, Readhead said.

Other speakers addressed the role in AD pathobiology of proteostasis, nitrosylation, microglia and the immune system, stress granules, autophagy, and the chaperome—that is, the suite of molecules that help proteins fold correctly. Greg Carter from the Jackson Laboratory, Bar Harbor, Maine, reviewed progress in the MODEL-AD project, which has released ApoE and TREM2 mouse models, including R47H and Y38C, and plans to issue eight to 10 new lines per year, including one that will have the complete tau locus humanized.

Ryan gave an overview of the new ACTC (Dec 2017 news), while Cynthia Musante from Pfizer in Cambridge, Massachusetts, championed the power of quantitative systems pharmacology as a means to better predict how modulation of drug targets translates into clinical endpoints. In the emerging therapeutics session, Frank Longo from Stanford, Roberta Brinton from the University of Arizona, and Mark Gurney from Tetra Discovery Partners in Grand Rapids, Michigan, shared data from early stage trials of p75 receptor antagonists to stem neurodegeneration, allopregnanolone to promote regeneration, and a phosphodiesterase 4D allosteric inhibitor to improve memory, respectively (Dec 2017 conference news; May 2017 conference news).

The full program and a videocast of Day 1 are available on the NIH website. —Tom Fagan

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NIH Summit Wraps Up with Recommendations for Research

01 Jun 2018

The third summit on AD since 2012, called NIH Alzheimer's Research Summit 2018: Path to Treatment and Prevention, was scheduled for March 1 and 2 at the institute's Bethesda campus in Maryland. Day one went off without a hitch (Mar 2018 conference news), but an overnight winter storm that closed the NIH campus left organizers scrambling to reschedule the second day. On May 24, with only panelists revisiting Bethesda, and all others attending by remote video link, the mission was complete. Over the two days more than 80 scientists had presented their and vision and weighed in on research priorities. With this, the NIH compiled a list of research recommendations centered on seven themes but organized under seven different headings. Confused? The nearly 100 published recommendations and sub-recommendations are grouped by the summit’s seven session titles:

Novel Mechanistic Insights into the Complex Biology and Heterogeneity of AD
Enabling Precision Medicine for AD
Translational Tools and Infrastructure for Predictive Drug Development
Emerging Therapeutics
Understanding the Impact of the Environment to Advance Disease Prevention
Advances in Disease Monitoring, Assessment, and Care
Building an Open Science Research Ecosystem to Accelerate AD Therapy Development

Yet they fall broadly into these seven themes:

Developing a better understanding of the complex and multifactorial causes of disease
Enabling precision medicine research needed to develop interventions that can address the underlying disease process, as well as the disease symptoms, and be tailored to a person’s unique disease risk profile for Alzheimer’s disease
Enhancing the research infrastructure and developing translational tools to accelerate therapy development
Supporting the development of novel therapeutics that target the many facets of Alzheimer’s disease
Understanding the impact of the environment and its interaction with genetic and biological factors to advance effective prevention strategies for Alzheimer’s disease
Leveraging emerging digital technologies and big data approaches to improve our ability to discover early markers of disease, better track responsiveness to treatment, and provide better care
Bringing together multiple stakeholders to build a new research ecosystem based on the principles of open science

The National Advisory Council on Aging adopted the new recommendations on May 23 and will use them to update milestones for the National Plan to Address Alzheimer’s Disease, which guides the nation’s research community toward finding ways to treat and prevent dementia by 2025.

Summit Day Two—Take Two
Day two picked up where day one had left off, discussing emerging therapeutic approaches. Researchers briefly reviewed non-amyloid-based therapies in early stage trials. Roberta Diaz Brinton, University of Arizona, Tucson, said her concept of regenerating the flailing brain was gaining traction, with allopregnanolone having just passed toxicology testing and now slated for a Phase 2 trial using a delayed-start, adaptive design. Allopregnanolone has pleiotropic effects, boosting neuro-, oligodendro-, and synaptogenesis, as well as mitochondrial respiration. Along similar lines, Mark Gurney, Tetra Discovery Partners, Grand Rapids, Michigan, announced a Phase 2 trial for the phosphodiesterase 4 inhibitor BPN14770. This drug boosts the CREB pathway, which is essential for early and late memory, and reportedly stabilizes synapses by ramping up production of brain-derived growth factor (BDNF; see Dec 2017 conference news). Mark Tuszynski, University of California, San Diego, also plans to boost BDNF, but by delivering the gene directly into the brain. Tuszynski pioneered this strategy using nerve growth factor, but that did not pan out as a viable treatment (Mar 2018 news). Targeting the gene to the right place in the brain was problematic, he said. For BDNF, he plans to use MRI imaging to guide placement of the engineered vector into the brain. Complementing these regenerative strategies, Frank Longo, Stanford University, Palo Alto, California, has developed a small molecule modulator of the neurotrophin p75 receptor. LM11A-31 counteracts degenerative signaling in the AD brain, appeared safe in a Phase 1 trial, and is now being tested in Phase 2A in Europe, Longo said in Bethesda.

Linda Van Eldik, University of Kentucky, Lexington, and Martin Watterson, Neurokine Therapeutics, Philadelphia, have collaborated for many years on developing drugs to tamp down inflammation in the brain. In Bethesda, Van Eldik reviewed MW151, a compound that came out of a functional screening program and blocks biosynthesis of cytokines. Van Eldik said MW151 is the first in its class, has good safety and metabolic profiles in preclinical testing, and she expects to file an Investigational New Drug application for it soon. Given orally at low doses, MW151 suppresses cytokine overproduction in mice, including two models of AD, but Van Eldik did not elaborate on how it works. Meanwhile, MW189, an intravenous formulation of MW151 that is being developed for acute conditions such as a traumatic brain injury or intracerebral hemorrhage, is finishing a Phase 1 study in healthy adults. Van Eldik told Alzforum she is seeking sponsorship to begin Phase 2 (May 2017 conference news). In giving an update on a third compound, MW150, Watterson said being a p38α kinase inhibitor it also suppresses cytokine production but by a different mechanism of action to MW151/189. He said preclinical toxicology raised no safety issues, and the compound is now being tested in Europe in people for the first time.

Michela Gallagher and colleagues at Johns Hopkins University, Baltimore, have adopted a different therapeutic strategy. They are trying to temper hyperactive neural circuits. Gallagher reviewed levetiracetam, an anticonvulsive medication being repurposed for use at low doses in dementia. It has been poised for Phase 3 testing for some time (Dec 2016 conference news). Then Gallagher introduced GABA-A α5-positive allosteric modulators, a new class of potential therapeutics for AD. Gallagher said that GABA-A α5 receptors are highly enriched on the same neurons that are overactive in prodromal AD, and that activating them boosts tonic inhibition of those same neurons. The NIH Blueprint Neurotherapeutics Network supports lead optimization in that program, Gallagher told Alzforum.

In another stab at repurposing, Alice Taubes, University of California, San Francisco, outlined how she screens for previously approved drugs that can reset AD-type transcriptomic profiles back to something that looks more normal. “In the age of big data, we can allow the brain to tell us what it needs, rather than trying to figure it out from the literature,” Taubes claimed. She integrates transcriptome profiles from large data sets, such as AMP-AD, to find consensus disease signatures, then looks for drugs that can normalize up- or downregulated genes. She has screened 13,000 compounds and is studying the top hit to find out how it works. Similarly, Rong Xu, a computer scientist from Case Western Reserve University, Cleveland, laid out how computational analysis followed by experimental testing might identify approved drugs that could benefit AD patients. Her goal is to review known drug side effects that indicate altered brain function, then test those drugs in mouse models to determine their mode of action.

In the remaining sessions, researchers focused on the importance of understanding environmental exposures in advancing disease prevention; advances in disease monitoring, assessment, and care; and how to build an open science research ecosystem to accelerate therapeutic development. As on day one, big data and advanced technologies were a common theme. For example, Kelly Bakulski, University of Michigan, Ann Arbor, stressed how little is known about the role of pollutants. She said the U.S. produces more than 85,000 different types of chemicals, of which only 300 have undergone rigorous health and safety testing by the Environmental Protection Agency, and only five have been banned outright. “We are vastly underinformed about the health consequences of chemicals in our everyday environment,” she said. Bakulski said that studying the “exposome” will be an important advance.

Xu stressed that big data and computational approaches can be brought to bear to understand how environmental exposure and genetics combine to affect dementia risk. With 85,000 chemicals and 30,000 genes, the permutations are almost incalculable, she said. Xu uses computational algorithms to crunch numbers from large data sets in search of clues to how chemicals affect brain function. She started with 171 metabolites from gut bacteria, combining chemical genetics and GWAS databases to predict how they might associate with diseases, including AD. Andrew Saykin, Indiana University, Indianapolis, emphasized the microbiome as well, noting that there are more microbes in a person’s gut than human cells in his or her body. Data from the ADNI and ROSMAP studies suggest correlations between secondary bile acids generated by the microbiome and cortical thickness, glucose metabolism, and longitudinal cognitive decline, Saykin said.

Looking at the bigger societal picture, Jennifer Manly from Columbia University, New York, noted how dementia incidence and risk factors can be dictated by race, ethnicity, and social demographics, which are all affected by the environment. Laura Baker, Wake Forest School of Medicine, Winston-Salem, North Carolina, reviewed the rationale behind POINTER, the U.S. multidomain intervention trial based on the FINGER trial in Europe (Aug 2017 conference news). Hiroko Dodge, Oregon Health & Science University, Portland, studies web-based tools that enhance social engagement. She described I-CONECT, a.k.a. the Internet-based Conversational Engagement Clinical Trial. It will test if 30-minute video chats two to four times a week over a year benefit cognition among socially isolated people aged 80 and older.

On the use of technology for monitoring, data collection, and intervention, Jeff Kaye, Oregon Health & Science University, Portland, reviewed the CART initiative, which stands for Collaborative Aging (in Place) Research Using Technology. This is a collaborative effort among academics, industry, and the NIH to develop tools for home monitoring. Kaye noted the challenges in setting up a system that relies on many moving parts, including computers, wearable sensors, home Wi-Fi devices, specialized software, all integrated with electronic health information and analysis. Nevertheless, he said, prototypes have been deployed to homes at four different sites around the U.S: Portland, Oregon; Northwest Virginia; Chicago; and Miami.

Mariana Figueiro from Rensselaer Polytechnic Institute, Troy, New York, outlined how one technological advance—tailored lighting—can improve circadian rhythm, sleep patterns, behavior, and mood in AD patients. Andrew Lim, University of Toronto, urged that wearable technologies and better animal models be used to study disturbances of sleep and circadian rhythm in dementia, while Daniela Brunner, founder and CEO of Early Signal, a nonprofit that develops smart technology to capture data from wearable devices, noted that device reliability, data collection and storage, and consent all still pose problems. On the latter, Dorothy Farrar-Edwards, University of Wisconsin, Madison, said that e-consent, which simplifies the often mind-boggling, booklet-sized consent forms, has enrolled almost 60,000 people and could be a useful tool for AD researchers. Ardy Arianpour, CEO and founder of Seqster, said his goal was to provide a means for people to own their own health data. People should be able to not only store the data in one place that’s accessible to researchers, but also to will it so that when they pass on the information is there for posterity.

In the last session, panelists led by Eric Reiman, Banner Alzheimer’s Institute, Phoenix, discussed how to build an open system that will accelerate research. Noting the success of ADNI, API, AMP-AD and other collaborative projects with commitments to open data sharing, Reiman stressed that going forward, it will be essential that scientists share data and samples from clinical trials and academic studies. It will be critical to do this in a productive and cordial way that values sharers, Reiman said. As an example, Lara Mangravite, from the nonprofit Sage Bionetworks, Seattle, noted that AMP-AD now shares 60,000 files from 42 investigators across 22 institutions with samples from 36 research studies. Suzana Petanceska, NIA, said that when the concept AMP-AD was first floated, some said this degree of sharing was a terrible idea for young investigators, who would be scooped. That has not happened. “I feel we often use young investigators as a human shield against data sharing,” said Petanceska. “I’m happy to say they are doing fine and several already have their own labs. It’s the rest of us who need to change.”—Tom Fagan

2018 Alzheimer’s Disease Research Summit

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