Federal Project Grant Award Summary

The National Institute on Aging (NIA) awarded the Regents of the University of Michigan a Project Grant totaling $298,419 under the Aging Research program (CFDA 93.866) for the period February 1, 2026 through January 31, 2031. This award funds the development of novel machine learning and statistical methodologies designed to analyze immune system data and enhance understanding of immunosenescence—the age-related decline of immune function—and its connection to age-related diseases. The research directly addresses analytical gaps in processing flow cytometry immune data, which are compositional, highly skewed, and subject to measurement errors that render standard analytical approaches unreliable.

The funded research consists of four primary aims: (1) developing a robust nonparametric framework to denoise immune cell frequency data independent of distributional assumptions; (2) creating a model-based clustering framework to identify immune subgroups while adjusting for covariates and identifying key drivers of heterogeneity; (3) developing semi-parametric methods to integrate multiple immune biomarkers and associate them with aging outcomes while emphasizing biological interpretability; and (4) additional methodological development not fully detailed in the provided summary. The project leverages data from large-scale epidemiological studies such as the Health and Retirement Study (HRS) to advance predictive modeling of disease risk and identification of therapeutic targets in aging populations. Research will be conducted at the University of Michigan's Ann Arbor campus.