What inspired you to pursue aging research?
I have a background in quantitative and statistical genetics, specifically focusing on developing methodsto detect and quantify the effects of genes that influence traits and disease. I became interested in aging research through a colleague who studies Alzheimer’s Disease and cognitive aging. I found the biology and the measures of aging fascinating, and also particularly well-suited to the types of methods I have been working on because of their tremendous complexity, involving many, many genes, complex molecular pathways, and non-genetic (environmental) influences. Beyond this research interest, aging-associated health outcomes pose a tremendous burden in terms of costs and suffering. Uncovering the basic biology of aging through new statistical genetic tools is a wonderful challenge that I hope can eventually lead to new therapeutic targets.
In your view, what does AFAR mean to the field, and what does it mean, for you, to receive an AFAR grant now?
AFAR is one of the preeminent research organizations on aging, and the research it sponsors will have a major impact on new therapies. To be selected for one of the Hevolution/AFAR New Investigator Awards is a true honor, one that will enable me and my lab to pursue complex models of frailty genetics in new ways. I am personally grateful to Hevolution/AFAR and the donors who help make my research possible.
What is exciting about your research’s potential impact?
The genomics revolution has truly been a revolution –every day we learn more about the complex systems that govern our genomes and how genetic variation influences aging and related traits. However, the statistical models we typically apply to ‘big data’ genomics datasets to identify genes that affect traits, including aging, have made a key, simplifying assumption: that every gene’s effect is independent from every other gene. We know that this does not reflect the biological pathways and complexity of aging, and these models have likely missed genes that integrate signals of pathways through their interactions with other genes. As hub genes, these may be some of the most important for understanding the biology of aging processes. In our work, the tools we apply incorporate these interactions into statistical models to analyze large genetic datasets from biobanks, bridging ‘big data’ with improved biological understanding, in hopes of identifying core genes involved in aging and the underlying biological processes they affect.
How would you describe your research to a non-scientist?
We test how genes act together to influence frailty, the increased vulnerability to potential stressors due to aging, using large biobanks that have electronic health records and genome-wide data for hundreds of thousands of participants. We hope to find key genes whose interactions with many other genes alter frailty risk for individuals, then identify thebiological processes that underlie that risk.
