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Blood Test May Detect Alzheimer’s Before Symptoms Appear

A new study demonstrates the promise of an early blood test for Alzheimer’s disease.

The results suggest that Alzheimer’s can be detected even before the onset of symptoms in people at genetic risk for the disease, according to researchers.

One of the greatest difficulties plaguing efforts to find effective treatments for Alzheimer’s is the enormous lag between the disease’s inception and the appearance of clinical symptoms, said Dr. Paul Coleman, an Alzheimer’s researcher at the Arizona State University Banner Neurodegenerative Disease Research Center (NDRC).

The researcher notes that the new method successfully distinguished between Alzheimer’s, Parkinson’s, and healthy controls, indicating that the test does not simply identify general phenomena of neurodegeneration, but is able to pick out Alzheimer’s  from other degenerative brain conditions.

“What we’ve done in our paper is to replicate our own work multiple times with different populations and even using different technologies,” Coleman said. “We also presented data showing the ability to detect people at risk of a future diagnosis for Alzheimer’s disease.”

The study, published in the journal Neurobiology of Aging, examined white blood cells or leucocytes. Here, segments of RNA known as transcripts, derived from specific DNA genes, hold vital clues regarding health, the researchers explain.

An early test is critical because scientists now know that by the time the first outward symptoms of Alzheimer’s appear, such as confusion, memory loss and other classic hallmarks, Alzheimer’s has been ravaging the brain for decades.

If the disease could be identified much earlier — close to its origin — there is hope that perhaps it could be slowed or even halted in its tracks, researchers noted.

Until now, however, efforts to develop a reliable early diagnostic for Alzheimer’s have not been successful, they said. Furthermore, the accuracy of the diagnosis even after the disease has entered its clinical phase remains poor.

It has long been known that Alzheimer’s produces changes in the brain, which can stimulate genes relating to conditions such as stress and inflammation. Expression of these genes appears in the blood in the form of specific RNA transcripts, the researchers explain.

The new study demonstrates that these RNA transcripts can be combined into an early diagnostic or biomarker, able to distinguish normal patients from those with Alzheimer’s or Parkinson’s disease and, most importantly, make accurate predictions about patients at risk for future development of Alzheimer’s disease, the researchers said.


The study divided 177 blood and 27 post-mortem brain samples into several groups, establishing that careful analysis of RNA transcripts in blood samples has the ability to distinguish early clinical AD, Parkinson’s disease (PD) and cognitively healthy patients.

It can accurately identify those carrying two copies of the APOE4 gene, known to be a severe risk factor for developing Alzheimer’s. Transcript screening was also used to identify those at risk for future cognitive impairment due to having at least one direct relative with AD.

The study managed to distinguish probable AD from normal controls with an accuracy of 93.8 percent, using just five RNA transcripts for the test.

The blood tests’ accuracy may be even higher as some of the “false positives” — healthy cases mischaracterized as AD — may be from subjects who are actually positive for pre-symptomatic manifestations of Alzheimer’s.

The results demonstrate that multivariate analysis of transcripts in blood samples provide an accurate and minimally invasive strategy for diagnosis of AD and early detection of AD risk.

Further, the results were consistent with examination of the same transcripts identified in the post-mortem brains of subjects with Alzheimer’s compared with those diagnosed with Parkinson’s disease and with normal controls.

In addition to RNA transcripts linked with inflammation and stress, the study examined a series of epigenetic transcripts, RNA sequences that have undergone post-transcriptional modification.

Results again found a strong correlation between the presence of these epigenetic markers and AD, implying they may also provide a compelling diagnostic tool, researchers noted.

Future refinements should sharpen the ability to accurately identify Alzheimer’s disease at an early stage prior to the onset of clinical symptoms in a primary care setting, with just a simple blood extraction, the researchers said.

Efforts to conduct long-term longitudinal studies and hunt for additional diagnostic transcripts should eventually be combined with testing of new therapeutics aimed at early intervention, they noted.

Intriguingly, one or more of the many existing drugs for Alzheimer’s which have failed in clinical trials may actually succeed in slowing or arresting Alzheimer’s if they can be delivered early enough in the disease process, the scientists observed.

Further, trials for new drugs targeting at-risk patients can be ramped up significantly if a simple, non-invasive blood test can replace costly imaging like positron emission tomography (PET) scans, they noted.

Source: Arizona State University

Photo: In a new study, ASU-Banner NDRC researcher Paul Coleman and his colleagues at ASU, Mayo Clinic, University of Rochester, Banner Alzheimer Institute and Barrow Neurological Institute describe a blood test to detect Alzheimer’s disease at a pre-symptomatic state. Credit: Jason Drees for the Biodesign institute.

Blood Test May Detect Alzheimer’s Before Symptoms Appear

Janice Wood

Janice Wood is a long-time writer and editor who began working at a daily newspaper before graduating from college. She has worked at a variety of newspapers, magazines and websites, covering everything from aviation to finance to healthcare.

APA Reference
Wood, J. (2018). Blood Test May Detect Alzheimer’s Before Symptoms Appear. Psych Central. Retrieved on September 28, 2020, from
Scientifically Reviewed
Last updated: 8 Aug 2018 (Originally: 27 Aug 2017)
Last reviewed: By a member of our scientific advisory board on 8 Aug 2018
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