Association of brain amyloidosis with the incidence and frequency of neuropsychiatric symptoms in ADNI: a multisite observational cohort study

Objective To investigate the relationship between amyloid burden and frequency of existing and incidence of new neuropsychiatric symptoms (NPS) in elderly with and without cognitive decline. Methods 275 cognitively normal controls (NC), 100 subjective memory complaint (SMC), 559 mild cognitive impairment (MCI) and 143 Alzheimer’s disease dementia subjects from the Alzheimer’s Disease Neuroimaging Initiative received (18F)-florbetapir positron emission tomography (PET) scans. Yearly neuropsychiatric inventory (Neuropsychiatric Inventory (NPI)/NPI-Questionnaire) data were collected from the study partners at each visit. Mean standard uptake volume ratios (SUVR) normalised to whole cerebellum were obtained. Positive amyloid PET scan was defined as mean SUVR ≥1.17. Fisher’s exact test was used to compare frequency and incidence between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate of neuropsychiatric symptoms (NPS) between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate hazard ratios for developing the most common NPS by amyloid status. Results No differences in NPS frequency were seen between amyloid positive and amyloid negative NC, SMC, MCI or dementia groups. MCI subjects with amyloid pathology however tended to have greater frequency x severity (FxS) of anxiety, hallucinations, delusions, apathy, disinhibition, irritability, aberrant motor behavior, and appetite, but not agitation, depression, night-time disturbances, or elation. MCI subjects with amyloid pathology were at greater risk for developing apathy, anxiety and agitation over time. Baseline presence of agitation and apathy and new onset agitation, irritability and apathy predicted faster conversion to dementia among MCI subjects. Conclusions Amyloid pathology is associated with greater rate of development of new NPS in MCI. Anxiety and delusions are significant predictors of amyloid pathology. Agitation, irritability and apathy are significant predictors for conversion from MCI to dementia

Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors

Die polnische Freiheit und Preußens Friedrich : Oder: Über die Furcht der Hohenzollern vor dem polnischen Freiheitsbazillus

Aus Anlass des 300. Geburtstags von „Friedrich dem Großen“ im Jahr 2012 erinnert der Autor daran, dass der Preußenkönig nicht nur ein Philosoph und Aufklärer war, sondern auch ein Verächter von „polnischer Freiheit“ und dass er mit seiner Politik erheblich zur deutsch-polnischen Verfeindung mit beigetragen hat

ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease

Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity. © 2013 The Authors

A Systematic Review of Cost-of-Illness Studies of Multimorbidity

Objectives: The economic burden of multimorbidity is considerable. This review analyzed the methods of cost-of-illness (COI) studies and summarized the economic outcomes of multimorbidity. Methods: A systematic review (2000–2016) was performed, which was registered with Prospero, reported according to PRISMA, and used a quality checklist adapted for COI studies. The inclusion criteria were peer-reviewed COI studies on multimorbidity, whereas the exclusion criterion was studies focusing on an index disease. Extracted data included the definition, measure, and prevalence of multimorbidity; the number of included health conditions; the age of study population; the variables used in the COI methodology; the percentage of multimorbidity vs. total costs; and the average costs per capita. Results: Among the 26 included articles, 14 defined multimorbidity as a simple count of 2 or more conditions. Methodologies used to derive the costs were markedly different. Given different healthcare systems, OOP payments of multimorbidity varied across countries. In the 17 and 12 studies with cut-offs of ≥2 and ≥3 conditions, respectively, the ratios of multimorbidity to non-multimorbidity costs ranged from 2–16 to 2–10. Among the ten studies that provided cost breakdowns, studies with and without a societal perspective attributed the largest percentage of multimorbidity costs to social care and inpatient care/medicine, respectively. Conclusion: Multimorbidity was associated with considerable economic burden. Synthesising the cost of multimorbidity was challenging due to multiple definitions of multimorbidity and heterogeneity in COI methods. Count method was most popular to define multimorbidity. There is consistent evidence that multimorbidity was associated with higher costs

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

In vivo detection of substantia nigra and locus coeruleus volume loss in Parkinson’s disease using neuromelanin-sensitive MRI: Replication in two cohorts

Patients with Parkinson’s disease undergo a loss of melanized neurons in substantia nigra pars compacta and locus coeruleus. Very few studies have assessed substantia nigra pars compacta and locus coeruleus pathology in Parkinson’s disease simultaneously with magnetic resonance imaging (MRI). Neuromelanin-sensitive MRI measures of substantia nigra pars compacta and locus coeruleus volume based on explicit magnetization transfer contrast have been shown to have high scan-rescan reproducibility in controls, but no study has replicated detection of Parkinson’s disease-associated volume loss in substantia nigra pars compacta and locus coeruleus in multiple cohorts with the same methodology. Two separate cohorts of Parkinson’s disease patients and controls were recruited from the Emory Movement Disorders Clinic and scanned on two different MRI scanners. In cohort 1, imaging data from 19 controls and 22 Parkinson’s disease patients were acquired with a Siemens Trio 3 Tesla scanner using a 2D gradient echo sequence with magnetization transfer preparation pulse. Cohort 2 consisted of 33 controls and 39 Parkinson’s disease patients who were scanned on a Siemens Prisma 3 Tesla scanner with a similar imaging protocol. Locus coeruleus and substantia nigra pars compacta volumes were segmented in both cohorts. Substantia nigra pars compacta volume (Cohort 1: p = 0.0148; Cohort 2: p = 0.0011) and locus coeruleus volume (Cohort 1: p = 0.0412; Cohort 2: p = 0.0056) were significantly reduced in the Parkinson’s disease group as compared to controls in both cohorts. This imaging approach robustly detects Parkinson’s disease effects on these structures, indicating that it is a promising marker for neurodegenerative neuromelanin loss

Fig 3 -

A comparison of mean SNc contrast in control (top row) and PD (bottom row) groups for both cohorts. Mean MTC images from cohort 1 are shown in the left column while mean MTC images from cohort 2 are shown in the right column. For each group, the mean MTC image was created by transforming MTC images from individual participants to MNI space and then averaging. Regions experiencing PD-related neuronal loss are indicated by yellow arrows in the bottom row.</p

Demographic information for the groups used in this analysis.

Demographic information for the groups used in this analysis.</p