Featured cohort: BioFIND
The BioFIND project contains resting-state MEG data and structural MRI data from more than 320 volunteers, approximately half with with mild cognitive impairment (MCI) – often an early stage of Alzheimer’s disease – and half who are healthy. The aim of the study is to evaluate potential MEG biomarkers of neurodegeneration, such as Alzheimer’s disease, with a view towards earlier detection and more efficient testing of potential new treatments.
A joint initiative between the University of Cambridge and the Technical University of Madrid, BioFIND is an open-science resource, and the data are available exclusively via the DPUK Data Portal.
We spoke to principal investigator Professor Rik Henson, of the MRC Cognition and Brain Sciences Unit in Cambridge, about the BioFIND project and the decision to share the data via DPUK.
Q&A with Professor Rik Henson
DPUK: Why is brain imaging such an important tool in efforts to tackle dementia?
Rik Henson: It’s generally accepted that the symptoms of dementia arise quite late in many of the diseases that cause it – including Alzheimer’s – but that changes in the brain occur at an earlier stage. We’ve previously been able to see these changes through structural MRI scans, but there are other emerging imaging techniques such as PET and MEG that could pick up signs of disease even earlier.
There’s hope, therefore, that these imaging modalities might show changes in synaptic function, well before the symptoms become clear. If we can detect disease earlier, we could potentially test treatments sooner – even revisiting drugs that may have failed to work previously because they were administered too late in the day, when toxic proteins had already built up and started killing brain cells. We could also use brain imaging to track whether new or repurposed treatments are having the desired effect. That’s the hope.
DPUK: Tell us about the BioFIND cohort.
RH: BioFIND is based on magnetoencephalography (MEG), which is a relatively recent technology. It allows you to look at brain function and is similar to electroencephalography (EEG), which has been around for a long time, but with greater spatial resolution. MEG has the potential to extract multiple functional networks in the brain.
To the best of our knowledge, there has previously been no large cohort of people with Alzheimer’s disease or MCI for whom MEG data has been obtained and shared. Our collaboration between Cambridge and Madrid has recruited, to date, 324 volunteers, but that’s just the start. We want to increase the size of the cohort, which will help machine learning algorithms extract as much value as possible – specifically new diagnostic features in the rich MEG data. We’d also love to make it longitudinal by following up with volunteers after several years to show change over time in brains that are ageing healthily versus those with progressive neurodegeneration.
MEG data are very rich, with around 300 sensors recording brain activity every millisecond. The more data you have, the more precise you can be when diagnosing disease or following the effects of drugs.
DPUK: Why did you decide to make the BioFIND data freely available on the DPUK Data Portal?
RH: I’m a strong believer in data sharing and open science. It’s vital in science that claims are based on evidence and can be checked by others. And I think the requirement to share data (and analysis code) makes researchers more likely to ensure their claims are robust.
DPUK is a great model for this and has the benefit that the BioFIND data can be used in approved research projects without ever being removed from the platform. That’s reassuring for our volunteers and means we’re creating as much value as possible from the data.
We’re grateful to the DPUK team for helping to make the dataset accessible, curating it into a format where it can be used and understood by researchers, and making sure the right software is available for analysis.
If you are a cohort PI who would like to explore sharing your data via DPUK, please contact us at email@example.com.