Alzheimer’s disease (AD) is a mental disorder that originates from the degeneration of neurons in the brain. The diagnosis of AD is significant to Canada because about 30% of people with dementia remain undiagnosed, yet it has debilitating effects on patients, resulting in increased medical costs and augmented caregivers’ demand (Manuel et al., 2016). Pathophysiology mechanism shows that AD occurs due to the deficiency of neurotransmitters, genetic mutations, deposition of amyloid-beta proteins, and aggregation of tau proteins (Kaufman et al.., 2016; Du et al., 2018). In their study, Kraus et al. (2019) targeted aggregated tau proteins as molecular markers using Alzheimer’s disease real-time quaking-induced conversion (AD RT-QuIC). Research findings demonstrated that AD RT-QuIC is a sensitive diagnostic and prognostic method for detecting the levels of aggregated tau proteins in cerebrospinal fluid. NIH/National Institute of Allergy and Infectious Diseases (2018) reported the research findings in the news article, Science Daily, that AD RT-QuIC is an ultrasensitive test that detect corrupted tau proteins for early diagnosis and effective treatment. Critical analysis of the news article shows that it provides accurate reporting and presentation of the primary research.
The news article accurately reports the focus of the study in the diagnosis of AD. NIH/National Institute of Allergy and Infectious Diseases (2018), study designed an ultrasensitive test for AD by detecting a degraded tau protein in the brain tissues. Based on research findings, it is true that the designed test is accurate in detecting aggregated tau proteins. Krau et al. (2019) established that AD RT-QuIC is a very sensitive method because it can detect tau aggregates obtained from the brain tissues in the dilution ranges between 10-7 and 10-10 proportions. Comparative analysis shows that the news article accurately reported that AD RT-QuIC is a very sensitive method with the ability to detect low concentrations of tau aggregates in the brain tissues.
The news article also offers an accurate reporting of the significance of the study’s findings. The sensitivity of the designed method is not only important to the early diagnosis of AD but also the development of novel treatment strategies (NIH/National Institute of Allergy and Infectious Diseases, 2018). As AD associates with other neurodegenerative disorders, it is difficult to detect and differentiate its pathophysiology. Moreover, previous methods of diagnosis relied on the syndromic definition of signs and symptoms, which only appear at the late stages of AD. Following the design of this method, it is now possible to diagnose AD at early stages using tau aggregates as biomarkers and evaluate the progression of treatment interventions (Kraus et al., 2019). Early diagnosis enhances the effectiveness of treatment interventions, while the degree of the aggregation of tau proteins shows the effects of treatments. Hence, the news article accurately presents that the diagnostic method is important in the diagnosis and prognosis of AD among patients.
The analysis of the news article reveals that it made key statements that are in line with the pathophysiology of AD. One key statement is that tau protein clusters are some of the targeted biomarkers used in the diagnosis of AD (NIH/National Institute of Allergy and Infectious Diseases, 2018). This statement highlights that the accumulation of tau isoforms in the brain with four-repeats (4R) and three-repeats (3R) relates to the manifestation of AD in individuals (Kraus et al., 2019). Moreover, the assessment of literature indicates that tau aggregates comprise a significant biomarker for AD. According to the tau hypothesis, AD stems from the aggregation of tau proteins in the brain tissues, resulting in the impairment of neuronal functions and neurodegeneration (Du et al., 2018; Sharma & Singh, 2016). Another key statement is that AD RT-QuIC is an ultrasensitive method of detecting aggregated tau proteins. When compared to the detection of A-beta amyloid proteins, tau deposition is a sensitive and selective biomarker for AD (Brier et al., 2016). Thus, these key statements in the news article have a scientific basis, which supports their description of the pathophysiology of AD.
The presented findings in the news article would enhance the diagnosis of AD in the generation population. Since the news article describes the designed diagnostic method as ultrasensitive, people with mental disorders would consider using it in the diagnosis of AD. Moreover, patients with AD and researchers because would use this method in the prognostic evaluation of treatment interventions. A critical analysis shows that the news article does not report the selectivity aspect of the method in the diagnosis and prognosis of AD. Overall, the news article has a positive impact on the diagnosis and monitoring of AD among patients.
The analysis of the news article reveals that it provides an accurate reporting of the research findings of the study. The news article highlights the sensitivity of the designed diagnostic method and its benefits in the diagnosis and prognosis of AD. Key statements in the news article that are in line with the pathophysiology of AD relate to the aggregation of tau proteins and their sensitivity in predicting and differentiating AD from other mental disorders. Therefore, the presented findings have significant benefits because they would enhance the diagnosis and treatment of AD, as well as improve the design of new drugs.
References
Brier, M. R., et al. (2016). Tau and A-beta imaging, CSF measures, and cognition in Alzheimer’s disease. Science Translational Medicine, 8(338), 1-9. Web.
Du, X. et al. (2018). Alzheimer’s disease hypothesis and related therapies. Translational Neurodegeneration, 7(2), 1-7. Web.
Kaufman, S. K.et al. (2016). Tau prion strains dictate patterns of cell pathology, progression rate, and regional vulnerability in vivo. Neuron, 92(4), 796-812. Web.
Kraus, A. et al. (2019). Seeding selectivity and ultrasensitive detection of tau aggregate conformers of Alzheimer’s disease. Acta Neuropathologica, 137, 585-598. Web.
Manuel, D. G. et al. (2016). Alzheimer’s and other dementias in Canada, 2011 to 2031: a microsimulation Population Health Modeling (POHEM) study of projected prevalence, health burden, health services, and caregiving use. Population Health Metrics, 14(37), 1-10. Web.
NIH/National Institute of Allergy and Infectious Diseases. (2018). Test detects protein associated with Alzheimer’s and CTE: Findings could lead to early diagnosis, better treatment studies.Science Daily. Web.
Sharma, N., & Singh, A. N. (2016). Exploring biomarkers for Alzheimer’s disease. Journal of Clinical and Diagnostic Research, 10 (7), 1-6. Web.