Blood-Based Test Developed for Diagnosing Alzheimer's Disease

Blood-based biomarkers for AD would have the important advantage of being safe, affordable, and easy to administer in large cohorts and/or in rural areas and therefore could have an enormous impact on clinical care and clinical trials alike.

A team of scientists led by those at the David Geffen School of Medicine at University of California (Los Angeles, CA, USA) developed a multimodal biomarker classifier for predicting brain amyloidosis using cognitive, imaging, and peripheral blood protein from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) mild cognitive impairment (MCI) cohort data. ADNI1 enrolled 398 subjects with MCI. The 151 subjects with MCI provided peripheral blood and CSF, but not Pittsburgh compound B-positron emission tomography (PiB-PET) data, were selected for inclusion in the training sample. Conversely, the 60 subjects with MCI who provided peripheral blood and PiB-PET imaging constituted the testing sample.

Apolipoprotein E (ApoE) genotyping was performed for all study participants using anti-coagulated blood samples. Quantitative polymerase chain reaction assays were used for genotyping ApoE nucleotides 334 T/C (rs 429358) and 472 C/T (rs 7412) with the ABI 7900 real-time thermocycler (Applied Biosystems; Foster City, CA, USA) using DNA freshly prepared from ethylenediaminetetraacetic acid (EDTA) treated whole blood. The team selected relevant peripheral blood proteins for inclusion in their model, ones where demonstrable aberrant levels of each of these proteins in peripheral blood in AD have found associations between their concentrations and subsequent cognitive decline and/or imaging change.

The results of the study suggest that plasma, imaging, and cognitive measures can be used to potentially predict brain amyloidosis with modest accuracy and confirm the AD relevance of interleukin 6 receptor (IL-6R) and clusterin, the two plasma measures that proved useful for this classification. For identification of subjects with MCI at greatest risk of disease progression to dementia, the self-tuning classifiers achieved reasonable but modest predictive accuracy.

Liana G. Apostolova, MD, MSc, the lead author of the study said, “Our study suggests that blood protein panels can be used to establish the presence of Alzheimer's-type pathology of the brain in a safe and minimally invasive manner. We need to further refine and improve on the power of this signature by introducing new disease-related metrics, but this indicates that such a test is feasible and could be on the market before long.” The study was published on February 17, 2015, in the journal Neurology.

Related Links:
David Geffen School of Medicine
Applied Biosystems