Israeli ınnovation targets Alzheimer’s ‘silent phase,’ offering potential for earlier detection

Israeli molecular imaging technology is helping scientists study one of the earliest and most elusive drivers of Alzheimer’s disease, potentially opening new avenues for earlier diagnosis and more targeted treatment, according to TPS-IL.

The technology, developed by Prof. Shai Rahimipour of Bar-Ilan University, played a central role in a new international study published in the peer-reviewed Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, led by researchers at the Icahn School of Medicine at Mount Sinai in New York together with collaborators from Bar-Ilan University and Canada. The researchers reported evidence that soluble amyloid-beta oligomers, small toxic protein clusters believed to contribute to Alzheimer’s disease years before symptoms appear, can damage brain cells long before they become detectable by today’s diagnostic methods.

Unlike the larger amyloid plaques detected by current PET scans, these oligomers remain largely invisible to existing clinical tools, making them one of the greatest challenges in Alzheimer’s research.

To address this challenge, Rahimipour and colleagues in Bar-Ilan University’s Department of Chemistry developed a family of cyclic peptides that selectively bind to amyloid-beta oligomers while largely ignoring the larger plaques. Tagged with fluorescent molecules or radioactive copper, the compounds allow researchers to visualize the toxic clumps in brain tissue and could eventually become next-generation PET imaging agents for Alzheimer’s disease.

In the new study, Dr. Michelle Ehrlich and Dr. Sam Gandy of the Icahn School, together with colleagues, used a specialized mouse model that accumulates soluble oligomers without forming conventional plaques. Rahimipour’s molecular probes allowed the team to identify and characterize the elusive aggregates, showing that they disrupt the mitochondria that power nerve cells and impair communication between neurons even before detectable inflammation develops.

“Our goal has always been to develop tools that detect the forms of amyloid-beta most closely associated with the earliest stages of Alzheimer’s disease,” Rahimipour said. “This study demonstrates how our technology can help reveal disease mechanisms that have remained hidden because existing diagnostic tools simply cannot see these toxic oligomers.”

The findings could also affect how physicians monitor recently approved anti-amyloid therapies, including Lecanemab and Donanemab. Physicians currently monitor treatment mainly through biomarkers that reflect amyloid plaques, even though toxic oligomers may appear much earlier and persist after treatment. Researchers said technology capable of directly detecting oligomers could provide a more accurate picture of disease progression and treatment response.

Alzheimer’s disease is believed to begin decades before symptoms emerge. According to the researchers, detecting oligomers during this silent phase could enable earlier intervention, improve patient selection for clinical trials, and provide more sensitive tools for evaluating new therapies.

The potential impact is significant: Alzheimer’s disease affects tens of millions of people worldwide. As populations age, the number of people affected is expected to rise substantially in coming decades.

The findings are based on laboratory and animal studies, and further research will be needed to determine whether the approach performs similarly in human patients.

Beyond the laboratory, Rahimipour’s technology is moving toward clinical development. His team co-founded ApexBio, a startup developing the cyclic peptide platform for both diagnostic and therapeutic uses in Alzheimer’s disease. The company is conducting advanced preclinical studies with the goal of entering first-in-human Phase 1 clinical trials.

The molecular probes are also being used by several research laboratories in North America.

If future clinical trials prove successful, the technology could allow physicians to detect Alzheimer’s-related changes years before symptoms appear and better monitor patients’ responses to treatment. Researchers also believe the platform could aid the development of future therapies.