Alzheimer's Detection Through Plasma Protein Changes Offer Clues To Early Diagnosis: Study

A new type of blood test that analyses the folding of amino acids rather than their amounts may detect earliest biological signs of Alzheimer's disease, according to a study. Analysis of blood plasma samples from over 500 individuals show that structural differences in three proteins -- one involved in immune signalling, another in protein folding, and a third that transports fats in bloodstream -- are strongly linked to Alzheimer's status, according to the findings published in the Nature Aging journal. Researchers, including those at The Scripps Research Institute, US, said structural differences of plasma proteins helped accurately distinguish cognitively normal individuals, from those with Alzheimer's and mild cognitive impairment -- the preceding stage.

The method could eventually allow early diagnosis and treatment, they said.

Alzheimer's disease is currently diagnosed by measuring amyloid plaques and tau tangles, formed due to accumulation of amyloid and tau proteins in one's brain -- in blood or spinal fluid.

However, the neurodegenerative condition is increasingly thought to involve a broader failure of proteostasis, a system responsible for keeping proteins properly folded and removing damaged ones, researchers said.

The system is said to become less effective with ageing, because of which proteins are more likely to fold incorrectly during formation or restructuring, they said.

"Many neurodegenerative diseases are driven by changes in protein structure. The question was, are there structural changes in specific proteins that might be useful as predictive markers?" senior author John Yates, a professor at The Scripps Research Institute, said.

The researchers proposed that if proteostasis is disrupted in the brain, similar structural changes might also appear in proteins circulating in blood.

Plasma samples from the participants were divided into three groups -- cognitively normal adults, individuals with mild cognitive impairment and patients diagnosed with Alzheimer's.

The analysis determined how exposed or buried certain specific areas were in three-dimensional amino acid chain, indicating changes to their structure. Machine learning, a form of artificial intelligence, was used to identify patterns connected to disease stage.

As Alzheimer's disease advanced, specific blood proteins became less structurally "open", with structural changes of three showing the strongest association with disease.

The proteins were C1QA, involved in immune signalling, clusterin, involved in protein folding and amyloid removal, and apolipoprotein B, which transports fats in the bloodstream and contributes to blood vessel health.

The structural changes proved to be more informative for identifying disease stage than simply measuring protein concentrations, researchers said.

"This multi-marker panel based on plasma protein structural alterations represents a promising diagnostic approach that may enhance early AD (Alzheimer's disease) detection and provide insights for clinical trials, improving therapeutic outcomes," the authors wrote. 

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