Xuanwu Hospital team finds specific metabolic markers for peripheral blood AD!

*For medical professionals only

Alzheimer's disease (AD) is the most common cause of cognitive impairment in older adults

In order to be able to detect the clues of AD early, many researchers are committed to discovering the early diagnostic basis for

In addition, the clinical symptoms, pathological manifestations, and biological markers of AD and other types of dementia overlap to a certain extent, and even if the above tests are completed, AD

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Different diseases can cause subtle changes in the biochemical metabolic pathways in the human body, and through the analysis of metabolites, it is possible to find clues to specific diseases, so some scientists have pinned their hopes on

Recently, Associate Professor Jia Longfei and his team from the Department of Neurology of Xuanwu Hospital of Capital Medical University published the latest research results

Screenshot of the first page of the paper

The researchers used three sets of clinical data for different phases

The first set of data came from 55 study subjects in Beijing (28 in the AD patient group and 27 in the healthy control group) and were used to screen for metabolite changes
associated with AD.

There were no significant differences
in the mean age and sex ratios between the AD patient group and the healthy control group.

At the same time, the APOEε4 allele frequency, MMSE score, and Aβ42/T-tau/P-tau levels in the AD group were higher than those in the control group (below
).

They then analyzed metabolomics results
from the AD and control groups.

Of the 847 metabolites detected in peripheral blood, the results showed that 7 substances in the AD group were elevated (red marker below) and 77 were decreased (green marker below
).

Based on the metabolomics results, the researchers selected 10 metabolites with the most pronounced declines and 7 elevated metabolites for the next stage of analysis
.

The researchers further analyzed whether the above-mentioned significantly altered metabolites could assist in the diagnosis of AD
.

The second set of data came from a total of 185 participants in Shandong, Henan and Guangxi (93 in the AD patient group and 92 in the healthy control group), and the metabolomics results were the same as
in the first group.

After the factors of age, sex and years of education were included, the results showed that the levels of four metabolites such as choline glycerophosphate and aspartic acid were increased, and the levels of 7 metabolites such as hexanoyl carnitine and 4-decenoyl carnitine were reduced, and these changes were clearly related to AD (as shown below
).

Elevated metabolites are: glycerophosphatecholine (A), aspartic acid (B), hydroxypalmitic acid (C), choline (D); Reduced metabolites are: hexanoyl carnitine (E), 4-decenoyl carnitine (F), tetradecanedien carnitine (G), piperine (H), decanoyl carnitine (I), levoacetyl carnitine (J), serotonin (K)

Further ROC analysis revealed that the area under the curve (AUC) value of the overall results of these 11 substance changes reached 0.
97, showing that it was possible to effectively distinguish between the AD group and the control group (left in the figure below).


In addition, the AUC value of each single substance is between 0.
63-0.
73, that is, the ability of a certain metabolite to distinguish AD is weak (right in the figure below
).

The above results suggest that one of these 11 metabolites is less helpful in diagnosing AD, and that their combination is effective in diagnosing AD
from a normal population.

Clinical diagnosis of AD requires careful differentiation from other types of dementia, such as vascular dementia (VaD), Parkinson's disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and Lewy body dementia (DLB).


Therefore, the researchers collected data from 357 study subjects from Beijing and further grouped them according to different types of dementia (76 people in the AD group, 50 people in the VaD group, 52 people in the PDD group, 52 people in the bvFTD group, 51 people in the DLB group, and 76 people in the healthy control group) to verify whether the above metabolites could effectively distinguish AD from
other dementias.

The results showed that most of the above 11 metabolites only changed in patients with AD, and the trend of change was consistent with the previous results (below
).

Other types of dementia also have their own characteristic changes, such as: glycerophosphatecholine is elevated in patients with PDD (A), aspartic acid is elevated in patients with DLB (B), choline is elevated in patients with VaD (D), and serotonin is elevated in patients with VaD and bvFTD (K).

RoC analysis results show that the changing combination of metabolites in these 11 can effectively distinguish between AD and control groups (Figure A below), AD and non-AD (Figure B below), as well as AD and other types of dementia (Figure C below
).

In summary, the combination of these 11 metabolites can accurately diagnose patients with AD from the normal population and can clearly distinguish between patients with AD and other types of dementia patients
.

This simple and feasible method can be used in clinical practice for the differential diagnosis of AD, facilitating the early diagnosis and treatment of
patients.

In addition, it can also be used to detect AD patients from normal groups, and may even be used for AD screening in large-scale elderly populations, effectively reducing family and social burdens
.

Let's look forward to more reliable evidence of this research, as well as broader practical applications in the
future.

References:

1.
Mapstone, M.
, et al.
, What success can teach us about failure: the plasma metabolome of older adults with superior memory and lessons for Alzheimer's disease.
 Neurobiol Aging, 2017.
51: p.
148-155.

2.
Jia, L.
, et al.
, A metabolite panel that differentiates Alzheimer's disease from other dementia types.
 Alzheimers Dement, 2022.
18(7): p.
1345-1356.

Responsible editor Wang Xuening