A European Academy of Neurology guideline on medical management issues in dementia

BACKGROUND AND PURPOSE: Dementia is one of the most common disorders and is associated with increased morbidity, mortality and decreased quality of life. The present guideline addresses important medical management issues including systematic medical follow‐up, vascular risk factors in dementia, pain in dementia, use of antipsychotics in dementia and epilepsy in dementia. METHODS: A systematic review of the literature was carried out. Based on the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework, we developed a guideline. Where recommendations based on GRADE were not possible, a good practice statement was formulated. RESULTS: Systematic management of vascular risk factors should be performed in patients with mild to moderate dementia as prevention of cerebrovascular pathology may impact on the progression of dementia (Good Practice statement). Individuals with dementia (without previous stroke) and atrial fibrillation should be treated with anticoagulants (weak recommendation). Discontinuation of opioids should be considered in certain individuals with dementia (e.g. for whom there are no signs or symptoms of pain or no clear indication, or suspicion of side effects; Good Practice statement). Behavioral symptoms in persons with dementia should not be treated with mild analgesics (weak recommendation). In all patients with dementia treated with opioids, assessment of the individual risk–benefit ratio should be performed at regular intervals. Regular, preplanned medical follow‐up should be offered to all patients with dementia. The setting will depend on the organization of local health services and should, as a minimum, include general practitioners with easy access to dementia specialists (Good Practice statement). Individuals with dementia and agitation and/or aggression should be treated with atypical antipsychotics only after all non‐pharmacological measures have been proven to be without benefit or in the case of severe self‐harm or harm to others (weak recommendation). Antipsychotics should be discontinued after cessation of behavioral disturbances and in patients in whom there are side effects (Good Practice statement). For treatment of epilepsy in individuals with dementia, newer anticonvulsants should be considered as first‐line therapy (Good Practice statement). CONCLUSION: This GRADE‐based guideline offers recommendations on several important medical issues in patients with dementia, and thus adds important guidance for clinicians. For some issues, very little or no evidence was identified, highlighting the importance of further studies within these areas

Role of Esrrg in the Fibrate-Mediated Regulation of Lipid Metabolism Genes in Human ApoA-I Transgenic Mice

We have used a new ApoA-I transgenic mouse model to identify by global gene expression profiling, candidate genes that affect lipid and lipoprotein metabolism in response to fenofibrate treatment. Multilevel bioinformatical analysis and stringent selection criteria (2-fold change, 0% false discovery rate) identified 267 significantly changed genes involved in several molecular pathways. The fenofibrate-treated group did not have significantly altered levels of hepatic human APOA-I mRNA and plasma ApoA-I compared with the control group. However, the treatment increased cholesterol levels to 1.95-fold mainly due to the increase in high-density lipoprotein (HDL) cholesterol. The observed changes in HDL are associated with the upregulation of genes involved in phospholipid biosynthesis and lipid hydrolysis, as well as phospholipid transfer protein. Significant upregulation was observed in genes involved in fatty acid transport and β-oxidation, but not in those of fatty acid and cholesterol biosynthesis, Krebs cycle and gluconeogenesis. Fenofibrate changed significantly the expression of seven transcription factors. The estrogen receptor-related gamma gene was upregulated 2.36-fold and had a significant positive correlation with genes of lipid and lipoprotein metabolism and mitochondrial functions, indicating an important role of this orphan receptor in mediating the fenofibrate-induced activation of a specific subset of its target genes.National Institutes of Health (HL48739 and HL68216); European Union (LSHM-CT-2006-0376331, LSHG-CT-2006-037277); the Biomedical Research Foundation of the Academy of Athens; the Hellenic Cardiological Society; the John F Kostopoulos Foundatio

Identification of sulfation sites of metabolites and prediction of the compounds’ biological effects

Characterizing the biological effects of metabolic transformations (or biotransformation) is one of the key steps in developing safe and effective pharmaceuticals. Sulfate conjugation, one of the major phase II biotransformations, is the focus of this study. While this biotransformation typically facilitates excretion of metabolites by making the compounds more water soluble, sulfation may also lead to bioactivation, producing carcinogenic products. The end result, excretion or bioactivation, depends on the structural features of the sulfation sites, so obtaining the structure of the sulfated metabolites is critically important. We describe herein a very simple, high-throughput procedure for using mass spectrometry to identify the structure—and thus the biological fate—of sulfated metabolites. We have chemically synthesized and analyzed libraries of compounds representing all the biologically relevant types of sulfation products, and using the mass spectral data, the structural features present in these analytes can be reliably determined, with a 97% success rate. This work represents the first example of a high-throughput analysis that can identify the structure of sulfated metabolites and predict their biological effects

Detecting frontotemporal dementia syndromes using MRI biomarkers

BACKGROUND: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. METHODS: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). RESULTS: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index. CONCLUSION: This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia

Evaluating combinations of diagnostic tests to discriminate different dementia types

INTRODUCTION: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. METHODS: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. RESULTS: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. DISCUSSION: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further

HIF-1 activation induces doxorubicin resistance in MCF7 3-D spheroids via P-glycoprotein expression: a potential model of the chemo-resistance of invasive micropapillary carcinoma of the breast

BACKGROUND: Invasive micropapillary carcinoma (IMPC) of the breast is a distinct and aggressive variant of luminal type B breast cancer that does not respond to neoadjuvant chemotherapy. It is characterized by small pseudopapillary clusters of cancer cells with inverted cell polarity. To investigate whether hypoxia-inducible factor-1 (HIF-1) activation may be related to the drug resistance described in this tumor, we used MCF7 cancer cells cultured as 3-D spheroids, which morphologically simulate IMPC cell clusters. METHODS: HIF-1 activation was measured by EMSA and ELISA in MCF7 3-D spheroids and MCF7 monolayers. Binding of HIF-1α to MDR-1 gene promoter and modulation of P-glycoprotein (Pgp) expression was evaluated by ChIP assay and FACS analysis, respectively. Intracellular doxorubicin retention was measured by spectrofluorimetric assay and drug cytotoxicity by annexin V-FITC measurement and caspase activity assay. RESULTS: In MCF7 3-D spheroids HIF-1 was activated and recruited to participate to the transcriptional activity of MDR-1 gene, coding for Pgp. In addition, Pgp expression on the surface of cells obtained from 3-D spheroids was increased. MCF7 3-D spheroids accumulate less doxorubicin and are less sensitive to its cytotoxic effects than MCF7 cells cultured as monolayer. Finally, HIF-1α inhibition either by incubating cells with 3-(5'-hydroxymethyl-2'-furyl)-1-benzylindazole (a widely used HIF-1α inhibitor) or by transfecting cells with specific siRNA for HIF-1α significantly decreased the expression of Pgp on the surface of cells and increased the intracellular doxorubicin accumulation in MCF7 3-D spheroids. CONCLUSIONS: MCF7 breast cancer cells cultured as 3-D spheroids are resistant to doxorubicin and this resistance is associated with an increased Pgp expression in the plasma membrane via activation of HIF-1. The same mechanism may be suggested for IMPC drug resistance

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study

Background and Purpose: In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. / Methods: 70 MS patients (median EDSS of 2.0 [range 0.0–6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on ‘unseen’ center. / Results: Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and −1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. / Conclusion: The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods

GxE Interaction Influences Trajectories of Hand Grip Strength

Age-related decline in grip strength predicts later life disability, frailty, lower well-being and cognitive change. While grip strength is heritable, genetic influence on change in grip strength has been relatively ignored, with non-shared environmental influence identified as the primary contributor in a single longitudinal study. The extent to which gene-environment interplay, particularly gene-environment interactions, contributes to grip trajectories has yet to be examined. We considered longitudinal grip strength measurements in seven twin studies of aging in the Interplay of Genes and Environment across Multiple Studies consortium. Growth curve parameters were estimated for same-sex pairs, aged 34–99 (N = 10,681). Fisher’s test for mixture distribution of within-monozygotic twin-pair differences (N = 1724) was performed on growth curve parameters. We observed significant gene-environment interaction on grip strength trajectories. Finally, we compared the variability of within-pair differences of growth curve parameters by APOE haplotypes. Though not statistically significant, the results suggested that APOE ɛ2ɛ2/ɛ2ɛ3 haplotypes might buffer environmental influences on grip strength trajectories.peerReviewe