The brain is the most complex organ in the human body. Understanding how its many parts function is crucial to treating a wide range of psychiatric illnesses, as well as improving our understanding of development and aging.
In the Yale School of Public Health’s Department of Biostatistics, Associate Professor Yize Zhao is developing innovative statistical and machine learning methods to advance our knowledge of how the intricate processes within our brains impact our mental and physical well-being, and how these processes contribute to debilitating diseases like Alzheimer’s and depression.
“I am very interested in brain connectivity, its molecular signatures, and how this influences our behavior,” said Zhao. “With the development of neuroscience, people are starting to realize the complexity of a nervous system highly relies on the interconnectivity of its neuronal units, and a collection of all those points of interconnectivity over the entire brain is called brain connectivity.”
A recent paper authored by Zhao and published in Journal of the American Statistical Association studied the genetic impact on brain structure connectivity characterized by white matter fiber tracts. Zhao and her team have developed a new analytical framework to link brain structure connectivity with whole genome variants. Though both data components are complex and massive, the research team successfully identified innovative and robust signals that could contribute to uncovering genetic underpinnings for brain structural alternation.
Zhao’s cutting-edge work on imaging genetics was also recognized in 2021, when she was awarded a $1.8 million grant from the National Institute on Aging for her novel integrative imaging genetics work entitled "Novel integrative imaging genetics analysis for Alzheimer’s disease risk and progression." In that project, to overcome current limitations in imaging genetics studies, Zhao developed a series of analytical models to characterize the pathological mechanism among multi-modal imaging, genetics, and risk and progression of Alzheimer’s disease.
“Alzheimer’s disease is a national priority with no cure, and effective strategies are urgently needed to discover new disease risk or protective biomarkers for drug development,” Zhao said. “The development of an advanced and powerful learning model could potentially uncover crucial yet hidden information and induce more plausible conclusions.”
Zhao has significant expertise in neurodegenerative disease and aging. She is affiliated with Yale Alzheimer’s Disease Research Center’s (ADRC) and is a recipient of the Yale ADRC Research Scholar Award.
“My interest in aging and Alzheimer’s disease began as a postdoctoral fellow when I had the opportunity to work with large Alzheimer’s disease datasets and had interactions with many other researchers in this field,” Zhao said. She received her PhD in biostatistics from Emory University and then became a joint postdoctoral fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill.
Zhao’s current research is multi-faceted. She focuses primarily on developing statistical and machine learning methods to analyze large-scale complex data (neuroimaging, -omics, EHRs), Bayesian methods, feature selection, predictive modeling, data integration, missing data, and network analysis. She is also a core faculty member of the Yale Center for Analytical Sciences (YCAS) and has an affiliation with the Center for Biomedical Data Science.
Zhao collaborates with many Yale researchers from different disciplines as well as researchers from other institutions. Within Yale, her collaborations extend into the fields of epidemiology, cancer, psychiatry, neurology, radiology, and neuroscience.
“We have a lot of complementary skills,” said Zhao. “I have been learning a lot about other clinical and biological areas from my collaborators, and they have been relying on me to provide more powerful statistical methods to analyze their complex data and interpret the findings.”
It is always exciting and inspiring to explore scientific questions together as an interdisciplinary team.
Zhao
“Each of us brings in our expertise and pushes toward the same objective from different paths.”
As a relatively new faulty member in the Department of Biostatistics, Zhao said she appreciates the support and nurturing she has received from her senior colleagues.
“All of my senior colleagues are stellar researchers,” she said. “They gave me suggestions and were role models for me on how to pursue a successful academic career.”
She also enjoys interacting and collaborating with her peers.
“We communicate and share a lot about both work and life,” Zhao said. As for her students and postdocs, Zhao said, “I enjoy working with them. I am doing my best to provide them with the research opportunities and guidance they need to help their future careers.”