Model illuminates Alzheimer's disease

10 October 2016 | Research
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New mathematical model explains why symptoms of Alzheimer's disease can be drastically different among patients

A mathematical model developed by Singapore and US researchers has shed light on why symptoms of Alzheimer’s disease can be drastically different among patients. The breakthrough work led by NUS may be applied to explain variability in other brain disorders, including autism and schizophrenia.

Alzheimer’s disease is a memory-destroying disorder that affects about 10 per cent of the elderly population. No cure exists currently, and accurate biomarkers are needed to help the early detection of at-risk individuals. The behavioural symptoms and brain atrophy — the loss of brain cells — can vary widely across patients, complicating diagnosis, treatment and prevention.

To approach this problem, NUS Electrical and Computer Engineering Assistant Professor Yeo Boon Thye Thomas, together with recent graduate Zhang Xiuming and PhD student Sun Nanbo, designed a statistical model based on probabilistic relationships between patients and brain atrophy. They applied it to magnetic resonance imaging scans of 188 Alzheimer’s disease dementia participants and 190 at-risk non-dementia participants from the North American Alzheimer’s disease Neuroimaging Initiative database.

The model unveils at least three atrophy patterns in different brain regions — cortical, temporal and subcortical — accounting for the heterogeneity in brain cells loss among Alzheimer’s disease patients. In both dementia patients and at-risk cognitively normal participants, the cortical atrophy pattern was associated with worse decline in executive function, or the ability to plan and accomplish goals, while the temporal atrophy pattern was associated with worse memory decline.

According to Asst Prof Yeo, patients with cortical atrophy are younger and diagnosed with Alzheimer’s disease at an earlier age. At-risk mild cognitively impaired participants with temporal atrophy are more likely to progress to Alzheimer’s disease. The framework can also be applied to understanding heterogeneous disorders, including autism and Parkinson’s disease.

In addition to the NUS authors, this research published in the Proceedings of the National Academy of Sciences is co-authored by Dr Beth Mormino, Dr Mert Sabuncu and Dr Reisa Sperling from Harvard Medical School.

Asst Prof Yeo also holds joint appointments at Duke-NUS Medical School, A*STAR-NUS Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Network Programme.