NIH program builds knowledge platform on Terra and Google Cloud to accelerate Parkinson’s Disease (PD) research

Innovative public-private partnership releases clinical and genomic datasets to help researchers identify promising biomarkers for drug therapies.

On November 15, 2019, the Accelerating Medicines Partnership—Parkinson’s Disease (AMP PD) realized the first phase of its five-year project to advance the development of treatments for Parkinson’s, a degenerative neurological disorder. Affecting 7-10 million people globally, PD is the second most common age-related neurodegenerative disorder, after Alzheimer’s Disease.

Now, with the launch of AMP PD’s online Knowledge Platform—built by Verily, an Alphabet company and AMP PD collaborator—researchers around the world can draw on de-identified clinical and genomic data from over 4,000 patients to collaborate on identifying biomarkers to improve diagnosis, prognosis, and treatments for the disease.

The important thing about AMP PD is the partnership. We have diverse groups coming together to work for a common goal, to advance science….That we were able to do it on such a scale is pretty remarkable. It’s a huge database with multiple types of data collected longitudinally, which makes it unique. We’re so proud of it.

Debra Babcock, M.D., Ph.D., Program Director for Systems and Cognitive Neuroscience at the NINDS and co-chair of AMP PD’s Steering Committee

Facilitating collaboration across institutions

Administered by the Foundation for the NIH (FNIH), AMP PD is part of the NIH’s STRIDES Initiative to advance cloud computing in scientific research through partnerships with commercial cloud providers. Since 2018, Google has worked with the STRIDES Initiative to provide support services for fostering collaboration across institutions, establishing common data privacy standards, standardizing and sharing resources, and pooling datasets. In November 2019, the consortium launched the Knowledge Platform with help and guidance from Verily. The Platform was developed in collaboration with the Broad Institute on the Terra biomedical research platform using Google Cloud. It will help AMP PD partners and registered researchers share de-identified data and findings to accelerate progress in understanding Parkinson’s Disease.

Parkinson’s Disease is a chronic, progressive neurological disorder characterized by physical symptoms like tremors, impaired balance, and cognitive deficits. Researchers have confirmed both environmental and genetic components, but much is still unknown about who is at risk, how the disease develops, and how to treat it. There are no viable clinical therapies yet, and the direct and indirect costs of the disease are estimated to reach $52 billion in the United States alone. AMP PD’s unprecedented release of a unified, harmonized dataset enables individual researchers to conduct their own state-of-the art analyses, which can help pharmaceutical companies design better clinical drug trials and implement them faster.

Expanding access to biomedical research by sharing datasets on Google Cloud

The Knowledge Platform consists of the public-facing Knowledge Portal for user access and resources, searchable datasets in Google Cloud Storage and BigQuery, and Terra workspaces with their own built-in datasets and tools to help researchers get started quickly on data analysis. Debra Babcock, M.D., Ph.D., Program Director for Systems and Cognitive Neuroscience at the NINDS and co-chair of AMP PD’s Steering Committee, reports that “the development process has been remarkably smooth and has proceeded rapidly.” Eline Appelmans, M.D., MPH, Project Manager of Neuroscience Research Partnerships at the FNIH, adds that the Platform has been immediately popular, with close to 2,000 users in its first two months.

AMP PD’s Knowledge Platform provides researchers with easy access to large datasets from four participating cohorts: the Michael J. Fox Foundation (MFJJ) and NINDS BioFIND, Brigham and Women's Hospital and Massachusetts General Hospital Harvard Biomarkers Study, NINDS Parkinson’s Disease Biomarkers Program, MJFF’s Parkinson’s Progression Markers Initiative. According to Dr. Appelmans, the Platform already contains the clinical records of 4,298 PD and control participants, including 8,356 RNA samples and 3,941 whole genome sequencing (WGS) samples. Storing these huge datasets on Google Cloud allows AMP PD to offer researchers convenient access through their own Google accounts. They can query the data in BigQuery and run Compute Engine virtual machine (VM) instances on demand, while only paying for the storage and compute they actually use.

Dr. Babcock says there are several benefits to their approach: “A lot of PD studies are done in small samples. But some of the genes involved are rare variants and you really need large samples for subtle differences to be obvious. Increasing sample sizes is key. Also, many studies are not longitudinal. The datasets we bring together are collected longitudinally so we can see how the disease progresses, which is an important problem for Parkinson’s disease. Our datasets also include multiple data types from the same patients, which is very unusual. Many studies look at only genomics or clinical information and we provide both.”

Moving forward together

Dr. Babcock and the team running AMP PD have ambitious plans for their project. They want to include additional data sets from clinical trials that cross-reference PD and dementia and broaden the scope of patient samples by adding more WGS data from sequencing initiatives in Europe, Africa, and Asia. “New populations are particularly important because they bring in new variants and increase sample size,” Dr. Babcock says. “We also have plans to add more biological data on our existing cohorts. For example, an unbiased proteomics analysis is already in process and then a targeted proteomics analysis is starting soon.”

In assessing AMP PD’s success so far, Dr. Babcock emphasizes the importance of having the perspectives of multiple stakeholders. “The important thing about AMP PD is the partnership,” she says. “We have diverse groups coming together to work for a common goal, to advance science. It required a great deal of collaboration and the partners have been very good at working together to build consensus. We’ve all been very pleased. That we were able to do it on such a scale is pretty remarkable. It’s a huge database with multiple types of data collected longitudinally, which makes it unique. We’re so proud of it.”

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