A literature review of AD7c-ntp as a biomarker for Alzheimer's disease

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Effects of Exercise on Urinary AD7c-NTP (Alzheimer-Associated Neuronal Thread Protein) Levels and Cognitive Function Among Active Korean Elderly: A Randomized Controlled Trial

Background

Alzheimer-associated neuronal thread protein (AD7c-NTP) has been demonstrated to have high diagnostic accuracy in differentiating Alzheimer's disease (AD) patients from healthy individuals. However, it is yet unclear whether exercise can lower the level of AD7c-NTP in urine among active Korean elderly.

Objective

To assess the effect of exercise on AD7c-ntp levels in urine and cognitive function among active Korean elderly.

Methods

In total, 40 Korean elderly (≥65 years) were divided into Active Control group (CG, n = 10), Aerobic exercise group (AG, n = 18), and combined Resistance/Aerobic exercise group (RAG, n = 12). A total of 12 weeks of exercise intervention was implemented. At week 0 and 12, cognitive performance (Korean Mini-Mental State Examination, Korean-Color Word Stroop test), grip strength, and body composition (muscle mass and body fat percentage) were measured. Also, a morning urine sample was obtained from each subject. The level of AD7c-NTP was measured using competitive enzyme-linked immunosorbent assay (ELISA).

Results

After 12 weeks of exercise intervention, there was a significant difference of AD7c-NTP levels between RAG and CG (p = 0.026), AG and CG (p = 0.032), respectively. Furthermore, the AD7c-NTP levels in urine showed negative correlation with K-MMSE scores (r = -0.390, p = 0.013) and grip strength (r = -0.376, p = 0.017), among all participants after exercise intervention.

Conclusions

This is the first study to investigate urine biomarker through exercise intervention. In future stuides, participants who have low cognitive function and low activity levels need to be recruited to observe more significant 'Exercise' effect.

Dry Chemistry-Based Bipolar Electrochemiluminescence Immunoassay Device for Point-of-Care Testing of Alzheimer-Associated Neuronal Thread Protein

In this study, we developed, for the first time, a novel dry chemistry-based bipolar electrochemiluminescence (ECL) immunoassay device for point-of-care testing (POCT) of Alzheimer-associated neuronal thread protein (AD7c-NTP), where the ECL signals were automatically collected and analyzed after the sample and buffer solutions were manually added onto the immunosensor. The proposed immunoassay device contains an automatic ECL analyzer and a dry chemistry-based ECL immunosensor fabricated with a screen-printed fiber material-based chip and a three-dimensional (3D)-printed shell. Each pad of the fiber material-based chip was premodified with certain reagents for immunoreaction and then assembled to form the ECL immunosensor. The self-enhanced ECL of the Ru(II)-poly-l-lysine complex and the lateral flow fiber material-based chip make the addition of coreactants and repeated flushing unnecessary. Only the sample and buffer solutions are added to the ECL immunosensor, and the process of ECL detection can be completed in about 6 min using the proposed automatic ECL analyzer. Under optimized conditions, the linear detection range for AD7c-NTP was 1 to 10⁴ pg/mL, and the detection limit was 0.15 pg/mL. The proposed ECL immunoassay device had acceptable selectivity, stability, and reproducibility and had been successfully applied to detect AD7c-NTP levels in human urine. In addition, the accurate detection of AD7c-NTP and duplex detection of AD7c-NTP and apolipoprotein E ε4 gene were also validated. It is believed that the proposed ECL immunoassay device may be a candidate for future POCT applications.

Prediction of transition from mild cognitive impairment to Alzheimer's disease based on a logistic regression-artificial neural network-decision tree model

AIM

To develop a logistic regression model, artificial neural network (ANN) model and decision tree (DT) model for the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) to compare the performance of the three models.

METHODS

A total of 425 patients with MCI were screened from the original cohort. The actual follow up included 361 patients, with AD as the outcome variable. Three kinds of prediction models were developed: a logistic regression model, ANN model and DT model. The performance of all three models was measured with accuracy, sensitivity, positive predictive value and area under the receiver operating characteristic curve.

RESULTS

A total of 121 patients with MCI developed AD, and the average conversion rate was 9.49% per year. The ANN model had higher accuracy (89.52 ± 0.36%), area under the receiver operating characteristic curve (92.08 ± 0.12), sensitivity (82.11 ± 0.42%) and positive predictive value (75.26 ± 0.86%) than the other two models. The first five important predictors of the ANN model were, in order, ADL score, age, urine AD-associated neuronal thread protein, alcohol consumption and smoking. For the DT model, they were age, activities of daily living score, family history of dementia, urine AD-associated neuronal thread protein and alcohol consumption. For the logistic regression model, they were age, sex, activities of daily living score, alcohol consumption and smoking.

CONCLUSION

The logistic regression, ANN and DT models performed well at predicting the transition from MCI to AD with ideal stability. However, the ANN model had the best predictive value. Increased age, activities of daily living score, urine AD-associated neuronal thread protein, alcohol consumption, smoking and sex were important factors. Geriatr Gerontol Int 2021; 21: 43-47.

Relationship between Urinary Alzheimer-Associated Neuronal Thread Protein and Apolipoprotein Epsilon 4 Allele in the Cognitively Normal Population

We investigated the relationship between urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) levels and apolipoprotein epsilon 4 (ApoE ɛ4) alleles, as well as other factors that cause cognitive decline, in the cognitively normal population. We recruited 329 cognitively normal right-handed Han Chinese subjects who completed ApoE gene testing and urinary AD7c-NTP testing. There was no significant difference in urinary AD7c-NTP levels between the normal control and subjective cognitive decline groups. Urinary AD7c-NTP levels were significantly higher in subjects with ApoE ɛ3/4 and 4/4 [0.6074 (0.6541) ng/mL] than in subjects without ApoE ɛ4 [0.4368 (0.3392) ng/mL and 0.5287 (0.3656) ng/mL], and urinary AD7c-NTP levels positively correlated with ApoE genotype grade (r = 0.165, p = 0.003). There were significant differences in urinary AD7c-NTP levels between subjects with and without a history of coronary heart disease or diabetes. Urinary AD7c-NTP levels were not related to years of education, nature of work, family history of dementia, a history of hypertension, stroke, anemia, or thyroid dysfunction. Urinary AD7c-NTP levels were positively correlated with ApoE grade in the cognitively normal population. The relationship between risk factors of cognitive decline and urinary AD7c-NTP levels provides a new way for us to understand AD and urinary AD7c-NTP.

Application of artificial neural network model in diagnosis of Alzheimer's disease

Background

Alzheimer’s disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explore early sensitive markers for AD.

Methods

A population based nested case-control study design was used. 89 new AD cases with good compliance who were willing to provide urine and blood specimen were selected from the cohort of 2482 community-dwelling elderly aged 60 years and over from 2013 to 2016. For each case, two controls living nearby were identified. Biomarkers for AD in urine and blood, neuropsychological functions and epidemiological parameters were included to analyze potential risk factors of AD. Compared with logistic regression, k-Nearest Neighbor (kNN) and support vector machine (SVM) model, back-propagation neural network of three-layer topology structures was applied to develop the early warning model. The performance of all models were measured by sensitivity, specificity, accuracy, positive prognostic value (PPV), negative prognostic value (NPV), the area under curve (AUC), and were validated using bootstrap resampling.

Results

The average age of AD group was about 5 years older than the non-AD controls (P < 0.001). Patients with AD included a significantly larger proportion of subjects with family history of dementia, compared with non-AD group. After adjusting for age and gender, the concentrations of urinary AD7c-NTP and aluminum in blood were significantly higher in AD group than non-AD group (2.01 ± 1.06 vs 1.03 ± 0.43, 1.74 ± 0.62 vs 1.24 ± 0.41 respectively), but the concentration of Selenium in AD group (2.26 ± 0.59) was significantly lower than that in non-AD group (2.61 ± 1.07). All the models were established using 18 variables that were significantly different between AD patients and controls as independent variables. The ANN model outperformed the other classifiers. The AUC for this ANN was 0.897 and the model obtained the accuracy of 92.13%, the sensitivity of 87.28% and the specificity of 94.74% on the average.

Conclusions

Increased risk of AD may be associated with higher age among senior citizens in urban communities. Urinary AD7c-NTP is clinically valuable for the early diagnosis. The established ANN model obtained a high accuracy and diagnostic efficiency, which could be a low-cost practicable tool for the screening and diagnosis of AD for citizens.

The association between urinary Alzheimer-associated neuronal thread protein and cognitive impairment in late-life depression: a controlled pilot study

Accumulation of tau protein is associated with both Alzheimer's disease (AD) and late-life depression (LLD). Alzheimer-associated neuronal thread protein (AD7c-NTP), which is closely linked with the tau protein, is elevated in the cerebrospinal fluid and urine of AD patients. This study examined the association between urinary AD7c-NTP and late-life depression with cognitive impairment. One hundred and thirty-eight subjects were recruited into late-life depression with cognitive impairment (LLD-CI, n=52), late-life depression without cognitive impairment (LLD-NCI, n=29), AD (n=27), and healthy control (HC, n=30) groups. The level of urinary AD7c-NTP was measured using the enzyme-linked immunosorbent assay method. The Montreal Cognitive Assessment scale (MoCA), Hamilton Rating Scale for Depression (HRSD) and Hamilton Anxiety Rating Scale (HAMA) were used to assess cognitive functions and depressive and anxiety symptoms in the AD and LLD groups. Urinary levels of AD7c-NTP in the LLD-CI group (1.0±0.7ng/ml) were significantly higher than both the LLD-NCI (0.5±0.3ng/ml) and HC groups (0.5±0.3ng/ml), but lower than in the AD group (1.6±1.7 ng/ml). No significant associations were found in the level of urinary AD7c-NTP in relation to age, gender, education and MoCA in the LLD-CI group. The level of urinary AD7c-NTP appears to be associated with cognitive impairment in late-life depression and may be a potential biomarker for early identification of cognitive impairment in LLD.

Current status of biomarker research in neurology

Neurology is one of the typical disciplines where personalized medicine has been recently becoming an important part of clinical practice. In this article, the brief overview and a number of examples of the use of biomarkers and personalized medicine in neurology are described. The various issues in neurology are described in relation to the personalized medicine and diagnostic, prognostic as well as predictive blood and cerebrospinal fluid biomarkers. Such neurological domains discussed in this work are neuro-oncology and primary brain tumors glioblastoma and oligodendroglioma, cerebrovascular diseases focusing on stroke, neurodegenerative disorders especially Alzheimer's and Parkinson's diseases and demyelinating diseases such as multiple sclerosis. Actual state of the art and future perspectives in diagnostics and personalized treatment in diverse domains of neurology are given.