INDIANAPOLIS — Researchers at the Indiana University School of Medicine have developed a new way to read the brain’s “energy network patterns,” revealing insights into the progression of Alzheimer's disease. This could help improve how doctors detect, stage and treat patients.
Through analyzing brain scans and blood tests from hundreds of people in the Alzheimer's Disease Neuroimaging Initiative database, the team, led by Paul R. Territo, PhD, and Juan Antonio Chong Chie, PhD, discovered how brain networks reorganize as the disease progresses. They recently published their findings in Alzheimer's & Dementia: The Journal of the Alzheimer's Association.
The team analyzed brain metabolic activity and the associated functional networks over the course of Alzheimer’s disease, which develops structures like a "city-wide power grid."
Territo, professor of medicine, said clinicians typically track glucose — the brain's main energy source — through imaging to investigate changes during disease; however, prior approaches largely focused on small clusters of brain regions without considering their network involvement. The research team used a method called metabolic functional connectomics, which implements graph theory to build "metabolic network maps" for people who were cognitively normal, had early or late mild cognitive impairment and had Alzheimer's disease and related dementias.
"These metabolic networks revealed that the number and strength of connections between brain regions do not simply decline in a straight line," said Chong Chie, postdoctoral research fellow in the Territo lab. "Instead, network density and connectivity followed a striking ‘W’ shaped pattern across disease stages, suggesting the brain undergoes phases of breakdown and compensation as it struggles to maintain its normal function."
The team found that memory, language and other cognitive functions often show increased metabolic demand in the early and mid-stages of cognitive decline, consistent with the brain "working harder" to compensate, Territo said. As the disease moves toward dementia, he said these same functions show a clear metabolic decline, while motor-related networks tend to remain relatively more active. This pattern may help explain why memory and language often deteriorate earlier than movement in many people diagnosed with Alzheimer’s disease.
Territo said they also saw clear differences in how brain networks organize and respond to disease, based on sex. In men, the number of network modules — clusters of regions in the brain that strongly interact — decreases in number and cohesion as the disease progresses.
In women, the number of modules increased with disease stage, leading to a more fragmented network structure, Territo said. According to the Alzheimer’s Association, nearly two-thirds of Americans living with the disease are women, and among those, women progress at a faster rate than men.
"These findings point to different disease patterns in male and female brains, which may help explain why women are disproportionately affected by Alzheimer’s disease," Territo said.
The researchers additionally measured the "shortest paths" between regions, which measure how efficiently information moves across the brain’s metabolic network. They discovered that path lengths get shorter during mild cognitive impairment, which suggests a period when networks work more efficiently and use more energy. During late mild cognitive impairment and Alzheimer’s disease, the paths lengthen again, and efficiency drops. These changes follow an "M" pattern, Territo said, with the largest peak occurring at the late mild cognitive impairment stage.
"These changes in path length and network organization were most noticeable during the transition states from early to late mild cognitive impairment, a stage that could be crucial for therapeutic intervention," Territo said.
Although the study analyzed existing data and requires additional validation for clinical use, Territo said it points to several promising directions for Alzheimer’s disease care, such as earlier and more precise disease staging, better clinical trial design through patient stratification, mechanism-guided therapies and more meaningful diagnostic readouts.
The researchers now plan to extend their work by combining common imaging tests with MRI-based measures of blood flow and will follow people over time to see how their personal brain network trajectories relate to cognitive decline and treatment response.
"If these studies are successful, this network-based approach could help transform Alzheimer’s from a disease diagnosed late, and tracked imprecisely, into one that can be monitored earlier, more accurately and in ways that directly guide therapy," Territo said.
About the Indiana University School of Medicine
The IU School of Medicine is the largest medical school in the U.S. and is annually ranked among the top medical schools in the nation by U.S. News & World Report. The school offers high-quality medical education, access to leading medical research and rich campus life in nine Indiana cities, including rural and urban locations consistently recognized for livability. According to the Blue Ridge Institute for Medical Research, the IU School of Medicine ranks No. 15 in 2025 National Institutes of Health funding among all public medical schools in the country.
Writer: Ben Middelkamp, bmiddel@iu.edu
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