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    Home > Active Ingredient News > Study of Nervous System > Predict Alzheimer's disease 17 years in advance! These two blood test indicators are expected to bring about a change in early diagnosis!

    Predict Alzheimer's disease 17 years in advance! These two blood test indicators are expected to bring about a change in early diagnosis!

    • Last Update: 2022-09-15
    • Source: Internet
    • Author: User
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    ▎ WuXi AppTec content team editor


    The World Health Organization (WHO) estimates that more than 55 million people worldwide suffer from dementia, and this number is expected to rise to 139 million



    Neurodegenerative lesions that cause AD are usually progressive and have developed for decades before the patient's disability



    Before the emergence of AD, which marker changes in human blood could be red flags? To confirm this, a team of researchers led by Professor Klaus Gerwert of the Center for Protein Diagnostics at the Ruhr University in Bochum, Germany, recently conducted an important study that analyzed the results of 17 years of follow-up to



    The research team found that in the 17 years before the clinical symptoms of AD, β the degree of amyloid (Aβ) misfolding can accurately predict its risk



    Screenshot source: Alzheimer's & Dementia


    The current view is that AD consists of a series of "continuum" lesions and can be classified according to the patient's biomarker status according to the ATN classification



    • A: Aβ changes, which can be detected by cerebrospinal fluid examination and PET;

    • T: hyperphosphorylated tau, which can be detected by cerebrospinal fluid examination and PET;

    • N: Neurodegeneration, which can be detected



    In addition, the current research on AD blood markers, such as Aβ1-42/Aβ1-40 ratio, phosphorylated tau (P-tau), neurofiber (NfL) and GFAP, has also achieved many results



    Previous studies have suggested that elevated blood levels of P-tau181, P-tau217, and P-tau231 not only suggest that the disease may be in a prodromal or mild cognitive impairment (MCI) phase, but also predict the pathological development of amyloid or tau proteins; NfL is highly correlated with neurodegenerative lesions overall, but lacks specific predictive power for the onset of AD; GFAP has demonstrated a potential ability
    to predict dementia as well as AD.

    It is worth noting that detection methods that combine different blood markers (e.
    g.
    , Aβ1-42/Aβ1-40 ratio, GFAP, and NfL) also show considerable potential
    to effectively identify brain amyloidosis and disease severity.

    In the current study, based on the study data from subjects in the ESTHER cohort (n=308), the researchers analyzed the association between the degree of Aβ misfolding (pathological changes in the early stages of AD disease) and plasma marker levels (P-tau181, GFAP, and NfL) levels, and explored effective predictors
    of AD diagnosis in the general population.

    In addition, the study included APOE ε4, a high-risk genotype for analysis
    .

    There were 68 participants in the ESTHER cohort who were diagnosed with AD during a 17-year follow-up period, and a further 240 subjects were classified as control populations
    .

    Based on immune infrared sensing technology, the researchers measured Aβ misfolding (amide I band)
    in the plasma of subjects.

    The results showed that the mean amide I maximum in AD patients was 1641 cm–1, while the average amide I maximum in the control group was 1646 cm–1
    .

    Immune infrared sensor readings were significantly lower in patients with AD compared to the control group, indicating that patients diagnosed with AD within 17 years had significantly higher levels of Aβ misfolding in their blood at baseline (P < 0.
    001
    ).

    In addition, the average P-tau181 in AD patients was significantly higher than that in the control group, at 2.
    3 pg/mL and 1.
    9 pg/mL (P < 0.
    01), respectively.
    There were also significant differences in the average GFAP between patients with AD and the control group, which were 159.
    0 pg/mL and 99.
    6 pg/mL (P<0.
    001, respectively).
    At baseline, NfL levels in patients with AD were also significantly increased (23.
    9 pg/mL) compared with the control group (18.
    9 pg/mL) (P < 0.
    001).


    The results of further analysis suggest that the degree of Aβ misfolding showed the highest accuracy in the prediction of AD diagnosis (OR=4.
    24), followed by APOE genotype (≥1 ε4 allele vs 0 ε4 alleles, OR=2.
    36) and GFAP levels (OR=2.
    08).


    In contrast, the NfL level (OR=1.
    37) and the P-tau181 level (OR=1.
    25) have lower
    accuracy.

    ▲Aβ misfolding degree combined with GFAP level can further improve the accuracy of AD prediction (Image source: Reference[1])

    In addition, the combination of GFAP and Aβ misfolding can further improve prediction accuracy (AUC increases to 0.
    83), while the addition of APOE genotypes does not further improve AUC
    .

    The paper emphasizes that the two markers of Aβ misfolding and GFAP level show a strong ability to predict the clinical occurrence of AD, or are important risk markers
    for early AD.

    In the future, these markers are expected to become an important initial screening method
    for the risk of AD in the elderly population.

    The researchers emphasize the importance
    of identifying individuals at high risk for AD for early intervention in the disease and for preventing the onset of symptomatic clinical AD.

    The current study, based on 17 years of follow-up results from a community population cohort, confirmed that combining Aβ misfolding and GFAP levels further improved the accuracy
    of AD predictions.

    Based on these two blood markers, the early diagnosis of AD in the future is expected to take non-invasive, more accessible and effective means to avoid lumbar puncture or PET imaging tests
    .

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