How to predict the risks of Alzheimer’s disease 17 years in advance!?

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How to predict the risks of Alzheimer’s disease 17 years in advance!?

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 How to predict the risks of Alzheimer’s disease 17 years in advance!?

New progress has been made in the diagnosis of Alzheimer’s disease (AD).

Recently, a research team led by Professor Klaus Gerwert of the Protein Diagnostic Center of Ruhr University Bochum, Germany , published important results in Alzheimer’s & Dementia [1].

The researchers found that the structural biomarker beta amyloid (Aβ) misfolding accurately predicted AD risk up to 17 years before AD clinical symptoms ;

Protein (GFAP) predicted the best results , followed by neurofibrils (NfL) and phosphorylated tau 181 (P-tau181).

In addition, Aβ misfolding combined with GFAP can further improve the accuracy of predicting AD in the asymptomatic stage .

Screenshot of the paper’s homepage

AD is the leading cause of dementia. According to the World Health Organization, more than 55 million people worldwide have dementia, and by 2050, this number is expected to rise to 139 million.

In 2019, the estimated global public health cost associated with dementia was $1.3 trillion [2].

There are currently about 10 million AD patients in some countries, and it is expected to increase to 30 million by 2050 [3].

Therefore, early detection and early treatment of AD are particularly important. In recent years, there has been an increasing number of studies using biomarkers to predict AD, and blood-based biomarkers are a non-invasive and cost-effective option.

The current ATN classification system based on biomarker status can be used as a diagnostic criterion for AD [4].

Biomarkers in this classification system include Aβ (A), hyperphosphorylated tau (T), and neurodegeneration (N), which can be detected by imaging, cerebrospinal fluid examination, and PET, but are costly and invasive Due to defects such as sex, the application is subject to certain restrictions.

There are also several concentration-based blood biomarkers, including Aβ1-42/Aβ1-40 ratio, phosphorylated tau (P-tau), NfL, and GFAP, etc., which can be quantified by immunoassay or mass spectrometry-based methods for Assist in the early diagnosis of AD.

The latest research also shows that plasma biomarkers can show pathological changes more than ten years before the appearance of AD clinical symptoms [5,6], which suggests that there is still an urgent need to develop new early diagnosis and treatment for AD. landmark.

Aβ misfolding in the early stage of disease has been identified as a structure-based AD biomarker [7], and Aβ misfolding in plasma can be directly measured by immuno-infrared sensor technology [8].

It has been found that plasma Aβ misfolding can predict the risk of AD diagnosis 14 years in advance in population-based cohort studies [9,10];

and in cohort studies of participants with subjective cognitive decline, it can also be Forecast 6 years in advance [8]. Therefore, Aβ misfolding has potential applications in predicting AD risk.

This study is based on a nested case-control study (ESTHER) of elderly Germans, including 68 AD patients (diagnosed with AD within 17 years), and 240 controls (general practitioner-confirmed no dementia diagnosis) , and collected baseline measurements of the four plasma biomarkers.

Baseline characteristics of the study population showed that the mean age of AD patients was 69 years, while the mean age of controls was 66 years, and 63% of AD patients and 53% of controls were female. In addition, 49% of AD patients and 28% of controls were APOE ε4 genotype-positive.

Baseline characteristics of the study population and association with a diagnosis of AD within 17 years

Using immuno-infrared measurement of Aβ misfolding, the researchers showed that AD patients had an average amide I maximum frequency of 1641 cm -1 (SD ± 4 cm -1 ), while controls had an average amide I maximum frequency of 1646 cm -1 ( SD ± 4 cm -1 ) . 1 ).

Compared with controls, the AD patient group had significantly lower immunoinfrared sensor readings, indicating that subjects diagnosed with AD within 17 years had higher levels of Aβ misfolding in their plasma at baseline .

Immunoinfrared sensor analysis of plasma Aβ misfolding in subjects at baseline

Next, the researchers found that the average level of P-tau181 in AD patients was 2.3 pg/mL (SD ± 1.4 pg/mL), which was significantly higher than the control group’s 1.9 pg/mL (SD ± 1.0 pg/mL).

The mean concentration of GFAP in AD patients was 159.0 pg/mL (SD ± 111.1), which was also significantly higher than that in the control group of 99.6 pg/mL (SD ± 46.7 pg/mL);

compared with the control group at baseline (18.9 pg/mL, SD ± 9.4 pg/mL), the NfL concentration in AD subjects was also significantly increased (23.9 pg/mL, SD ± 11.8 pg/mL).

Measurements of P-tau181, NfL and GFAP in plasma at baseline

Logistic regression analysis showed that the odds ratio (OR) of Aβ misfolding reduction per SD was the highest in predicting AD , 4.24 (95%CI: 2.68-6.67), followed by APOE per SD increase (2.36, 95%CI: 1.32) -4.24) and GFAP (2.08, 95% CI: 1.44-3.01).

In contrast, NfL (1.37, 95%CI: 0.98-1.91) and P-tau181 (1.25, 95%CI: 0.93-1.68) had lower ORs.

Receiver operating curve (ROC) analysis showed that the area under the curve (AUC) for Aβ misfolding was the highest among all biomarkers at 0.78 (95%CI: 0.71-0.85); while among the concentration markers, The AUC of GFAP was the highest at 0.74 (95%CI: 0.67-0.82), followed by NfL (AUC 0.68, 95% CI: 0.61-0.75) and P-tau181 (AUC 0.61, 95%CI: 0.53-0.70).

In addition, the combination of GFAP and Aβ misfolding could further improve the prediction accuracy, increasing the AUC to 0.83 (95% CI: 0.76-0.89), while the addition of APOE did not further improve the AUC.

Discriminatory power of ROC analysis biomarkers in AD patients (diagnosed within 17 years) and controls

It is worth noting that the diagnosis of dementia in this study may not have been accurate because not all subjects had seen a neurologist or other specialist.

In addition, the concentration values ​​of Aβ1-40 and Aβ1-42 could not be measured, so that the comparability between the structure and concentration changes of Aβ could not be analyzed, and further research is needed.

In conclusion, Aβ misfolding and GFAP have a strong ability to predict the risk of clinical AD, and can be used as potential biomarkers for early AD risk prediction.

References:

[1] Beyer L, Stocker H, Rujescu D, et al. Amyloid-beta misfolding and GFAP predict risk of clinical Alzheimer’s disease diagnosis within 17 years [published online ahead of print, 2022 Jul 19]. Alzheimers Dement. 2022;10.1002/ alz.12745.doi:10.1002/alz.12745

[2] Greenblatt C, World Health Organization. Dementia. [September 28, 2021]; Available from: https://www.who.int/news-room/fact-sheets/detail/dementia

[3] Wang Yingquan, Liang Jinghong, Jia Ruixia, Xu Yong. Prediction of the prevalence of Alzheimer’s disease in China from 2020 to 2050 [J]. Alzheimer’s Disease and Related Diseases, 2019, 2(01): 289-298 .

[4] Jack CR Jr, Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535-562. doi:10.1016/j. jalz.2018.02.018

[5] de Wolf F, Ghanbari M, Licher S, et al. Plasma tau, neurofilament light chain and amyloid-β levels and risk of dementia; a population-based cohort study. Brain. 2020;143(4):1220- 1232. doi:10.1093/brain/awaa054

[6] Rajan KB, Aggarwal NT, McAninch EA, et al. Remote Blood Biomarkers of Longitudinal Cognitive Outcomes in a Population Study. Ann Neurol. 2020;88(6):1065-1076. doi:10.1002/ana.25874

[7] Nabers A, Hafermann H, Wiltfang J, Gerwert K. Aβ and tau structure-based biomarkers for a blood- and CSF-based two-step recruitment strategy to identify patients with dementia due to Alzheimer’s disease. Alzheimers Dement (Amst) . 2019;11:257-263. Published 2019 Mar 12. doi:10.1016/j.dadm.2019.01.008

[8] Stockmann J, Verberk IMW, Timmesfeld N, et al. Amyloid-β misfolding as a plasma biomarker indicates risk for future clinical Alzheimer’s disease in individuals with subjective cognitive decline [published correction appears in Alzheimers Res Ther. 2021 Jan 15;13 (1):25]. Alzheimers Res Ther. 2020;12(1):169. Published 2020 Dec 24. doi:10.1186/s13195-020-00738-8

[9] Nabers A, Perna L, Lange J, et al. Amyloid blood biomarker detects Alzheimer’s disease. EMBO Mol Med. 2018;10(5):e8763. doi:10.15252/emmm.201708763

[10] Stocker H, Nabers A, Perna L, et al. Prediction of Alzheimer’s disease diagnosis within 14 years through Aβ misfolding in blood plasma compared to APOE4 status, and other risk factors. Alzheimers Dement. 2020;16(2):283 -291.doi:10.1016/j.jalz.2019.08.189

How to predict the risks of Alzheimer’s disease 17 years in advance!?

(source:internet, reference only)

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