Longitudinal study of Alzheimer’s biomarkers Analyses – Medical Science Assignment Help

Task 

Longitudinal study of Alzheimer’s biomarkers, allostatic load, and cognition among memory clinic patients.

Introduction: Allostatic load (AL) is defined as the cumulative dysregulation of neuroendocrine, immunological, metabolic and cardiovascular systems that increase the susceptibility to stress-related health problems. Several dementia and Alzheimer’s disease (AD) risk factors have been identified, yet little is known about the role of AL and its associations with AD biomarkers (e.g., beta-amyloid (A?) or tau) and cognitive function among memory clinic patients. Hence, this study aims to assess the association between AL and AD biomarkers, cognitive performance, and cognitive decline after 3-years of follow-up. 

Materials and methods: Data from 188 memory clinic patients were derived from the Cortisol and Stress in AD (Co-STAR) study in Sweden. Participants underwent baseline assessments including blood tests for AL measures (including cortisol, thyroid stimulating hormone, cobalamin, homocysteine, leukocytes, glycated hemoglobin, albumin, high-density and low-density lipoprotein cholesterol, triglycerides, and creatinine), cerebrospinal fluid (CSF) sampling for AD biomarkers and neuropsychological tests including five cognitive domains. Linear regressions were conducted, adjusting for age, sex, and education. 

Study design and participants 
This study is based on the Cortisol and Stress in Alzheimer’s disease (Co-STAR) study, a longitudinal observational study investigating the role of stress and lifestyle factors among patients referred to the Memory Clinic at the Karolinska University Hospital, Huddinge (Sweden). 
Patients aged 45 years and above attending their first visit at the Karolinska University Hospital Memory Clinic (between 2014 and 2017) were invited to participate in the study.  Exclusion criteria were severe sensory impairments (e.g., cognitive, visual, or auditory) or other conditions that would compromise their ability to participate, or conditions affecting hypothalamic-pituitary-adrenal (HPA)-axis activity (e.g. Cushing’s disease). A total of 233 participants agreed to participate, and 188 participants provided sufficient data for inclusion in this study. For the follow-up assessments between February 2018 and May 2019, 123 participants were invited, and 68 participated in the follow-up assessments, after 32 months on average.

Ethical considerations
The Co-STAR study received ethical approval by the Regional Ethical Review Board (Stockholm) (reference number: (2014/524-31/1). Participants were only included in the data collection if they provided written informed consent. 

Procedures 
At the baseline assessment, eligible patients had undergone routine clinical assessments at the memory clinic. This included the collection of information on demographic factors, medical exams, blood samples, measures of cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), genetics, and a comprehensive neuropsychological test battery.  Dementia diagnosis was based on criteria of the International Classification of Diseases 10 revision (24), diagnosis for mild cognitive impairment (MCI) was given according to criteria by Winblad and colleagues (25), which include subjective cognitive complaints, impairment on cognitive tests, no major impairments in daily life activities, and no dementia. 

Subjective Cognitive Impairment (SCI) was diagnosed when neither dementia nor MCI criteria were fulfilled, but the participant reported cognitive impairment.  Co-STAR participants were additionally provided with a kit for salivary cortisol sampling at home. Participants were instructed to provide saliva samples at six time points on two non-consecutive weekdays. Sampling time points were upon awakening (t1), 30 minutes (t2) and 60 minutes (t3) after awakening, at 2:00 P.M. (t4), at 4:00 P.M. (t5), and before going to bed (t6). To avoid contamination, participants were asked not to eat or brush their teeth before sampling. Participants were also provided with journals to document the exact sampling time.

Cognitive performance
The cognitive performance domains processing speed, memory, working memory, perceptual reasoning and general cognitive functioning, were measured using a comprehensive battery of neuropsychological tests. The memory score was based on four tests related to memory performance: the Rey Auditory Verbal Learning Test (delayed recall) (26), the Rey Complex Figure test (delayed recall) (27), the Digit Symbol test (28), and the Hagman test immediate recall which was developed and is used at the Karolinska University Hospital memory clinic, Huddinge for the assessment of visual memory. 
A composite working memory score was calculated from Wechsler’s Adult Intelligence Scale Digit Span and Arithmetic, processing speed was assessed with the Wechsler’s Adult Intelligence Scale Digit Symbol Substitution Test (29).  

Perceptual reasoning was assessed with the perceptual reasoning index from the Wechsler’s Adult Intelligence Scale (Block Design and Matrix Reasoning) (29). The general cognitive functioning score was obtained using four Wechsler Abbreviated Scale of Intelligence (WASI) tests (Block Design, Similarities, Matrix Reasoning, and Information) (30). Two of these tests are related to verbal cognition (Similarities and Information), while the other two are related to non-verbal cognition (31). Follow-up data on memory and perceptual reasoning was collected.

Allostatic load index
The AL index was constructed using 16 biomarkers derived from patients’ electronic health records collected within one year prior to the memory clinic visit based on the cut-off points summarized in Supplement Table 1. Variables which were included in the calculation of AL were: systolic blood pressure (SBP), diastolic blood pressure (DBP), cortisol awakening response (CAR; calculated using t1 and t2), cortisol afternoon level (calculated by averaging t5 & t6), cortisol bedtime level (t6), total cortisol output (area under the curve with respect to ground (AUCg), constructed using t1, t2, t4, t5, t6), thyroid stimulating hormone (TSH), cobalamin, homocysteine, leukocytes, glycated hemoglobin (HbA1C), albumin, high-density lipoprotein (HDL) cholesterol, Low-density lipoprotein (LDL) cholesterol, triglycerides, and creatinine.

The AL index score was calculated based on the count of AL biomarkers falling into the high-risk zone, and can range from 0 (lowest risk) to 16 (highest risk). The definition of high-risk zones is based on previous research conducted with the count-based AL index (8). Participants received a score of one for values above the 75th percentile (high levels) on seven biomarkers (HbA1c, LDL cholesterol, Creatinine, Triglycerides, Homocysteine, SBP, and DBP), values below the 25th percentile (low levels) on three biomarkers (Albumin, HDL, and Cobalamin), values below the 12.5th for Leukocytes and values below the 12.5th or above the 87.5th percentile (high and low levels) on five biomarkers (CAR, cortisol afternoon level, cortisol bedtime level, AUCg cortisol, and TSH) considering that  both hypo and hyper states may have negative health effects (8).  For all values that fall within normal ranges, the number zero was assigned. Subsequently, all biomarker scores were added to provide the AL index (ranging from 0 to 16) with higher scores representing greater physiological dysregulation.

AD-related biomarkers 
Three CSF biomarkers (A?1-42, T-tau, and P-Tau) within the standard assessment protocol at the Karolinska University Hospital memory clinic were included. CSF was obtained by lumbar puncture and A?1-42, t-tau and p-tau were measured using procedures previously described for A?1-42(32) and for t-tau and p-tau(33) . 

Data analyses 
Before conducting the statistical analyses, diagnostic analyses with the Shapiro-Wilk test were performed to ascertain whether the scores were normally distributed. Additionally, each regression model was tested for multicollinearity using the Variance Inflation Factor statistic, homoscedasticity generating a scatter plot with standardized residuals versus standardized predictors, and independence of errors by applying the Durbin- Watson statistic. Zero-skewness log-transformations were performed for T-tau and P-tau due to non-normal distribution. The AL index can range between 0-16. The mean AL of the study sample was 5.1 (SD=1.8), with scores ranging from 1 to 9. In this sample, the distributions of the AL scores were not normally distributed. However, the kurtosis and skewness were in the acceptable range (skewness=-0.164, kurtosis=-0.673).

Descriptive analysis was performed of all baseline variables and cognitive performance outcomes. We generated the relative frequency of the AL score by using histograms and calculated mean AL score. We then described the baseline characteristics of the study participants using counts and percentages for categorical variables and means and standard deviations (SDs) for continuous variables. Linear regression analyses were performed to assess the associations between AL, cognition, and AD biomarkers. Analyses were adjusted for age, sex, and education (the standard covariates in the AL and cognitive impairment literature (8)). The statistical analyses were performed using the IBM SPSS Statistics for Mac (Version 27.0) program, except for zero skewness log transformations that was performed with STATA 15.
 

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