Disease progression model in subjects with mild cognitive impairment from the Alzheimer’s disease neuroimaging initiative: CSF biomarkers predict population subtypes. Br J Clin Pharmacol

Johnson & Johnson Pharmaceutical Research & Development, Raritan, New Jersey, Titusville, New Jersey, and Spring House, Pennsylvania, USA.
British Journal of Clinical Pharmacology (Impact Factor: 3.88). 01/2013; 75(1). DOI: 10.1111/j.1365-2125.2012.04308.x


• Amnestic mild cognitive impairment MCI) represents the prodromal stage of Alzheimer's dementia and this disease progresses in a non-linear fashion.
• Disease progression depends on a variety of demographic, biochemical, genetic and cognitive factors.
• Baseline CSF biomarkers carry information about disease pathology and critical thresholds for these markers (Aβ and p-tau181P) have been identified that allow segregation of the population into MCI progressers and non-progressers.
AIM The objective is to develop a semi-mechanistic disease progression model for mild cognitive impairment (MCI) subjects. The model aims to describe the longitudinal progression of ADAS-cog scores from the Alzheimer's disease neuroimaging initiative trial that had data from 198 MCI subjects with cerebrospinal fluid (CSF) information who were followed for 3 years.
METHOD Various covariates were tested on disease progression parameters and these variables fell into six categories: imaging volumetrics, biochemical, genetic, demographic, cognitive tests and CSF biomarkers.
RESULTS CSF biomarkers were associated with both baseline disease score and disease progression rate in subjects with MCI. Baseline disease score was also correlated with atrophy measured using hippocampal volume. Progression rate was also predicted by executive functioning as measured by the Trail B-test.
CONCLUSION CSF biomarkers have the ability to discriminate MCI subjects into sub-populations that exhibit markedly different rates of disease progression on the ADAS-cog scale. These biomarkers can therefore be utilized for designing clinical trials enriched with subjects that carry the underlying disease pathology.

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Available from: Victor Lobanov, Mar 13, 2015
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    • "This is based on the Pittsburgh compound B-Positron emission tomography (PIB-PET) substudy of the 301/302 studies (n 5 154) where a total of 6.5% of APOE ε4 carriers and 36.1% of APOE ε4 noncarriers were amyloid negative at baseline[11]. Recently, Samtani et al.[6]have shown that amyloid-negative patients do not exhibit decline in ADAS-cog/11 and the current model allows zero progression rate (and even improvement in cognition). This is possible through covariate effects such as comedication status and allowing the random effect on the slope parameter to be additive in nature allowing progression rate to positive, zero, and negative at the individual level. "
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    ABSTRACT: To estimate longitudinal changes in disease progression (measured by Alzheimer's disease assessment scale-cognitive 11-item [ADAS-cog/11] scale) after bapineuzumab treatment and to identify covariates (demographics or baseline characteristics) contributing to the variability in disease progression rate and baseline disease status.
    Full-text · Article · Oct 2015
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    • "Simulation models applied to normal individuals, and those with mild cognitive impairment or AD, are a key step in the early detection and tracking of AD. In this context, disease progression models focusing on cognitive deterioration, as measured by a longitudinal response using the AD assessment scale-cognitive subscale (ADAS-cog), are well-accepted [5] [6] [7] [8] [9]. However, models characterizing functional decline in AD are not available to date. "
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    ABSTRACT: Objective Disability assessment for dementia (DAD) measurements from two phase-3 studies of bapineuzumab in APOE ε4 noncarrier and carrier Alzheimer's disease (AD) patients were integrated to develop a disease progression model. Methods We evaluated longitudinal changes in DAD scores, baseline factors affecting disease progression, and bapineuzumab effect on disease progression. Results A beta regression model best described DAD disease progression. The estimated treatment effect of bapineuzumab was not significant, consistent with lack of clinical efficacy observed in the primary analysis. The model suggested that progression of DAD tended to decrease with increase in bapineuzumab exposure. The exposure-response relationship was similar regardless of APOE ε4 status but more pronounced in patients with mild AD. Baseline disease status, age, memantine use, and years since onset (YSO) had significant effects on baseline DAD scores. AD concomitant medication use, baseline disease status, and YSO had significant effects on disease progression rate, measured by DAD score. Conclusions The beta regression model is a sensible modeling approach to characterize functional decline in AD patients. This analysis suggested a possible effect of bapineuzumab exposure on DAD progression. Further evaluation may be warranted in future studies. Trial Registration identifier: NCT00575055 and NCT00574132.
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    • "Biomarkers that can be utilized as surrogate markers of underlying pathological change have become of central importance for detection of early and preclinical AD. Efforts have been made by researchers worldwide to identify and validate different biomarkers for the early diagnosis and/or prediction of progression from MCI to AD, including positron emission tomography (PET) imaging ligands , archetypically Pittsburgh compound B (PiB), which bind to amyloid-(A), PET imaging with 18 F-FDG to measure local glucose metabolism [7] [8] [9] [10], structural magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biochemical biomarkers, especially A 1-42 , total tau (t-tau), and tau phosphorylated at threonine 181 (p-tau 181 ) either alone, or in combination with imaging and CSF biomarkers [11] [12] [13] [14]. It has been reported that the combination of increased CSF concentrations of t-tau or p-tau 181 and decreased concentration of A 1-42 improves sensitivity and specificity in the diagnosis of AD, and that these markers are predictive of future conversion from MCI to AD [15] [16] [17] [18]. "
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    ABSTRACT: Alzheimer's disease (AD) is the most common form of dementia, with no disease-modifying treatment yet available. Early detection of patients at risk of developing AD is of central importance. Blood-based genetic signatures can serve as early detection and as population-based screening tools. In this study, we aimed to identify genetic markers and gene signatures associated with cerebrospinal fluid (CSF) biomarkers levels of t-tau, p-tau181, and with the two ratios t-tau/Aβ1-42 and p-tau181/Aβ1-42 in the context of progression from mild cognitive impairment (MCI) to AD, and to identify a panel of genetic markers that can predict CSF biomarker p-tau181/Aβ1-42 ratio with consideration of APOE4 stratification. We analyzed genome-wide the Alzheimer's Disease Neuroimaging Initiative dataset with up to 48 months follow-up. In the first part of the analysis, the main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed for each of the four CSF biomarkers. In the second part of the analysis, we performed an integrated analysis of genome-wide association study results with pathway enrichment analysis, predictive modeling and network analysis in the subgroup of APOE4-negative subjects. We identified a panel of five SNPs, rs6766238, rs1143960, rs1249963, rs11975968, and rs4836493, that are predictive for p-tau181/Aβ1-42 ratio (high/low) with a sensitivity of 66% and a specificity of 70% (AUC 0.74). These results suggest that a panel of SNPs is a potential prognostic biomarker in APOE4-negative MCI patients.
    No preview · Article · Feb 2015 · Journal of Alzheimer's disease: JAD
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