Q&A with Brain Health Expert Dr. James Galvin
University of Miami Miller School of Medicine neurologist Dr. James Galvin explains how the Brain Health Index uses machine learning to track brain health over time and uncover early signs of cognitive decline.
Six years ago, when James Galvin, M.D., M.P.H., first presented at the annual AD/PD™ conference, he introduced the University of Miami’s Healthy Brain Initiative and outlined the ambitious goal of finding a coherent way to measure brain health and follow it over time.
Now, Dr. Galvin, professor of neurology at the Miller School, chief of the Cognitive Neurology Division, founding director of the Comprehensive Center for Brain Health and director of the Lewy Body Dementia Research Center of Excellence, has returned with findings that move the work forward. In this year’s oral presentation, he shared how his team is using the Brain Health Index to quantify brain health, predict cognitive change and begin uncovering the biological mechanisms that may explain why some people develop disease and others do not.
He sat down to discuss his team’s latest findings and what they mean for the future of brain health research.
Tell us about your AD/PD oral presentation.
My presentation focused on something we developed called the Brain Health Index. This gives us a single score, from 0 to 100, that reflects an individual’s overall brain health. It incorporates resilience factors, vulnerability factors and measures of brain performance. Using machine learning, we can generate a single score and follow it over time.
What makes the Brain Health Index so useful?
It gives us a practical way to measure brain health quickly and consistently. We can do this assessment in under 15 minutes and it has worked across all groups we have studied so far.
Because the score ranges from 0 to 100, we can define thresholds for low brain health, high brain health and the middle range. That allows us to compare people across groups and follow changes over time. Having a single metric makes those comparisons much easier and more meaningful.
What have you found so far in your research?
We’ve shown that healthy controls have the highest brain health scores while people with dementia have the lowest. We also found that people who perform normally on testing but report subjective cognitive complaints often have lower brain health scores than those without such complaints. That suggests the index may capture meaningful changes even before more obvious impairment appears.
Because we have followed people over time, we can see how their scores change. People who remained cognitively normal started with the highest scores and stayed relatively stable over a three-year period. Those who were impaired and became more impaired started lower and declined further. People in the middle range were especially interesting because many later converted and declined over time. Some with mild cognitive impairment improved. That opens the door to building predictive models that may help us understand who is likely to decline and who may remain stable or even improve.
How are you using this work to study underlying biological mechanisms?
We used two approaches, proteomics and epigenomics. Proteomics looks at patterns of protein expression. When we compared people with high brain health to those with low brain health, we identified 19 proteins that differed between the groups. Many have been linked either to pathways that increase Alzheimer’s disease risk or to processes that may be neuroprotective. Epigenomics looks at DNA methylation, one of the mechanisms that can turn genes on or off.
Along with my colleague, Dr. Deirdre O’Shea, we identified 135 epigenetic sites across 11 genes that were associated with the Brain Health Index, many of which appeared consistently across different models and were strongly correlated with brain health.
Five findings converged across both approaches, meaning the proteomic and epigenomic data pointed to the same proteins and pathways. These were linked to cellular structure and integrity, transcriptional regulation, neurotransmitter-related processes and neuroinflammation. That gives us greater confidence that we are identifying meaningful biological pathways involved in brain health.
Why do these findings matter?
This gives us a way to track people over time, make predictions about future decline and begin identifying the biological pathways involved. If those pathways can be defined clearly, they may eventually become druggable targets. That raises the possibility of developing treatments that could slow, stop or even reverse disease processes.
What do you most appreciate about this AD/PD conference?
It has been rewarding to return each year and share how our work has evolved. This meeting is especially valuable because it spans many neurodegenerative conditions, so it’s a great opportunity to learn what is happening in related fields and see how ideas and discoveries connect across disorders. Conferences also offer the chance to build new collaborations and have conversations that often lead to fresh ideas.
Tags: Alzheimer's disease, brain health, cognitive decline, Comprehensive Center for Brain Health, dementia, Department of Neurology, Dr. James Galvin, epigenome, greenness, Lewy body dementia, neurology, Newsroom, stroke