82 research outputs found

    PARTIAL LEAST SQUARES ON DATA WITH MISSING COVARIATES: A COMPARISON APPROACH

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    The correlation between any two random variables can be estimated using a variety of techniques including parametric methods based on the Pearson correlation coefficient, nonparametric methods, and regression analysis. While these estimators have been widely used, the computation of these estimates in the presence of missing data has not been as widely studied. There has been some work addressing the estimation of parameters in the presence of missing data for regression analysis; including imputation, inverse probability weighted regression and weighted estimating equations. However, there has been little work focused on the estimation of the correlation coefficient. To assess the usefulness of these methods in a practical setting, we present simulation studies comparing imputation, inverse probability weighting and complete cases and provide recommendations on the basis of these results. Furthermore, computation of Partial Least Squares (PLS) scores with the correlation matrix computed using the above mentioned techniques are also presented. We apply these results in a positron emission tomography data set consisting of several different brain regions as response variables and cognitive tasks as covariates of interest. Alzheimer's disease is a progressive and fatal health disease. The application presented in this work is significant for public health since it provides us with a better understanding of variability in different brain regions as it relates to neuropsychological tests that are helpful in diagnosis of progressive brain disease (i.e Alzheimer's disease)

    Acute Regression in Down Syndrome.

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    BACKGROUND: Acute regression has been reported in some individuals with Down syndrome (DS), typically occurring between the teenage years and mid to late 20s. Characterized by sudden, and often unexplained, reductions in language skills, functional living skills and reduced psychomotor activity, some individuals have been incorrectly diagnosed with Alzheimer's disease (AD). METHODS: This paper compares five individuals with DS who previously experienced acute regression with a matched group of 15 unaffected individuals with DS using a set of AD biomarkers. RESULTS: While the sample was too small to conduct statistical analyses, findings suggest there are possible meaningful differences between the groups on proteomics biomarkers (e.g., NfL, total tau). Hippocampal, caudate and putamen volumes were slightly larger in the regression group, the opposite of what was hypothesized. A slightly lower amyloid load was found on the PET scans for the regression group, but no differences were noted on tau PET. CONCLUSIONS: Some proteomics biomarker findings suggest that individuals with DS who experience acute regression may be at increased risk for AD at an earlier age in comparison to unaffected adults with DS. However, due to the age of the group (mean 38 years), it may be too early to observe meaningful group differences on image-based biomarkers

    T1 independent, T2* corrected chemical shift based fat-water separation with multi-peak fat spectral modeling is an accurate and precise measure of hepatic steatosis

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    Purpose: To determine the precision and accuracy of hepatic fat-fraction measured with a chemical shift-based MRI fat-water separation method, using single-voxel MR spectroscopy (MRS) as a reference standard. Materials and Methods: In 42 patients, two repeated measurements were made using a T 1-independent, T2 *-corrected chemical shift-based fat-water separation method with multi-peak spectral modeling of fat, and T 2-corrected single voxel MR spectroscopy. Precision was assessed through calculation of Bland-Altman plots and concordance correlation intervals. Accuracy was assessed through linear regression between MRI and MRS. Sensitivity and specificity of MRI fat-fractions for diagnosis of steatosis using MRS as a reference standard were also calculated. Results: Statistical analysis demonstrated excellent precision of MRI and MRS fat-fractions, indicated by 95% confidence intervals (units of absolute percent) of [-2.66%,2.64%] for single MRI ROI measurements, [-0.81%,0.80%] for averaged MRI ROI, and [-2.70%,2.87%] for single-voxel MRS. Linear regression between MRI and MRS indicated that the MRI method is highly accurate. Sensitivity and specificity for detection of steatosis using averaged MRI ROI were 100% and 94%, respectively. The relationship between hepatic fat-fraction and body mass index was examined. Conclusion: Fat-fraction measured with T1-independent T 2*-corrected MRI and multi-peak spectral modeling of fat is a highly precise and accurate method of quantifying hepatic steatosis. © 2011 Wiley-Liss, Inc

    White matter microstructure associations to amyloid burden in adults with Down syndrome.

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    INTRODUCTION: Individuals with Down syndrome (DS) are at an increased risk of developing Alzheimer's Disease (AD). One of the early underlying mechanisms in AD pathology is the accumulation of amyloid protein plaques, which are deposited in extracellular gray matter and signify the first stage in the cascade of neurodegenerative events. AD-related neurodegeneration is also evidenced as microstructural changes in white matter. In this work, we explored the correlation of white matter microstructure with amyloid load to assess amyloid-related neurodegeneration in a cohort of adults with DS. METHODS: In this study of 96 adults with DS, the relation of white matter microstructure using diffusion tensor imaging (DTI) and amyloid plaque burden using [11C]PiB PET were examined. The amyloid load (AβL) derived from [11C]PiB was used as a global measure of amyloid burden. AβL and DTI measures were compared using tract-based spatial statistics (TBSS) and corrected for imaging site and chronological age. RESULTS: TBSS of the DTI maps showed widespread age-by-amyloid interaction with both fractional anisotropy (FA) and mean diffusivity (MD). Further, diffuse negative association of FA and positive association of MD with amyloid were observed. DISCUSSION: These findings are consistent with the white matter microstructural changes associated with AD disease progression in late onset AD in non-DS populations

    Potential Utility of Plasma P-Tau and Neurofilament Light Chain as Surrogate Biomarkers for Preventive Clinical Trials

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    OBJECTIVE: To test the utility of longitudinal changes in plasma phosphorylated tau 181 (p-tau181) and neurofilament light chain (NfL) as surrogate markers for clinical trials targeting cognitively unimpaired (CU) populations. METHODS: We estimated the sample size needed to test a 25% drug effect with 80% of power at a 0.05 level on reducing changes in plasma markers in CU participants from Alzheimer's Disease Neuroimaging Initiative database. RESULTS: We included 257 CU individuals (45.5% males; mean age = 73 [6] years; 32% β-amyloid [Aβ] positive). Changes in plasma NfL were associated with age, whereas changes in plasma p-tau181 with progression to amnestic mild cognitive impairment. Clinical trials using p-tau181 and NfL would require 85% and 63% smaller sample sizes, respectively, for a 24-month than a 12-month follow-up. A population enrichment strategy using intermediate levels of Aβ PET (Centiloid 20-40) further reduced the sample size of the 24-month clinical trial using p-tau181 (73%) and NfL (59%) as a surrogate. DISCUSSION: Plasma p-tau181/NfL can potentially be used to monitor large-scale population interventions in CU individuals. The enrollment of CU with intermediate Aβ levels constitutes the alternative with the largest effect size and most cost-effective for trials testing drug effect on changes in plasma p-tau181 and NfL

    Astrocyte biomarker signatures of amyloid-β and tau pathologies in Alzheimer’s disease

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    Astrocytes can adopt multiple molecular phenotypes in the brain of Alzheimer's disease (AD) patients. Here, we studied the associations of cerebrospinal fluid (CSF) glial fibrillary acidic protein (GFAP) and chitinase-3-like protein 1 (YKL-40) levels with brain amyloid-β (Aβ) and tau pathologies. We assessed 121 individuals across the aging and AD clinical spectrum with positron emission tomography (PET) brain imaging for Aβ ([18F]AZD4694) and tau ([18F]MK-6240), as well as CSF GFAP and YKL-40 measures. We observed that higher CSF GFAP levels were associated with elevated Aβ-PET but not tau-PET load. By contrast, higher CSF YKL-40 levels were associated with elevated tau-PET but not Aβ-PET burden. Structural equation modeling revealed that CSF GFAP and YKL-40 mediate the effects of Aβ and tau, respectively, on hippocampal atrophy, which was further associated with cognitive impairment. Our results suggest the existence of distinct astrocyte biomarker signatures in response to brain Aβ and tau accumulation, which may contribute to our understanding of the complex link between reactive astrogliosis heterogeneity and AD progression

    Astrocyte reactivity influences amyloid-β effects on tau pathology in preclinical Alzheimer's disease

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    An unresolved question for the understanding of Alzheimer's disease (AD) pathophysiology is why a significant percentage of amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes unleash Aβ effects in pathological tau phosphorylation. Here, in a biomarker study across three cohorts (n = 1,016), we tested whether astrocyte reactivity modulates the association of Aβ with tau phosphorylation in CU individuals. We found that Aβ was associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau-positron emission tomography analyses revealed an AD-like pattern of tau tangle accumulation as a function of Aβ only in CU Ast+ individuals. Our findings suggest astrocyte reactivity as an important upstream event linking Aβ with initial tau pathology, which may have implications for the biological definition of preclinical AD and for selecting CU individuals for clinical trials
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