49 research outputs found
Analytical and clinical validation of a blood progranulin ELISA in frontotemporal dementias
Heterozygous mutations in the granulin (GRN) gene may result in haploinsufficiency of progranulin (PGRN), which might lead to frontotemporal dementia (FTD). In this study, we aimed to perform analytical and clinical validation of a commercial progranulin kit for clinical use. Analytical validation parameters including assay precision, selectivity, measurement range, dilution linearity, interferences and sample stability were tested according to previously described procedures. For clinical validation, PGRN levels were measured in plasma from 32 cognitively healthy individuals, 52 confirmed GRN mutation carriers, 25 C9orf72 mutation carriers and 216 patients with different neurodegenerative diseases of which 70 were confirmed as non-mutation carriers. Among the analytical validation parameters, assay precision and repeatability were very stable (coefficients of variation <7 %). Spike recovery was 96 %, the measurement range was 6.25-400 μg/L and dilution linearity ranged from 1:50-1:200. Hemolysis did not interfere with progranulin levels, and these were resistant to freeze/thaw cycles and storage at different temperatures. For the clinical validation, the assay was capable of distinguishing GRN mutation carriers from controls and non-GRN mutation carriers with very good sensitivity and specificity at a cut-off of 57 μg/L (97 %, 100 %, respectively). In this study, we demonstrate robust analytical and diagnostic performance of this commercial progranulin kit for implementation in clinical laboratory practice. This easy-to-use test allows identification of potential GRN mutation carriers, which may guide further evaluation of the patient. This assay might also be used to evaluate the effect of novel PGRN-targeting drugs and therapies
Public preferences for digital health data sharing: Discrete choice experiment study in 12 european countries
Background: With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public s views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level. Objective: This study investigated public preferences for digital health data sharing. Methods: A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class s pooled and regional data sets. Results: A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: A national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions. Conclusions: This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe
The impact of antiretroviral therapy on iron homeostasis and inflammation markers in HIV-infected patients with mild anemia
Genomewide association study for onset age in Parkinson disease
<p>Abstract</p> <p>Background</p> <p>Age at onset in Parkinson disease (PD) is a highly heritable quantitative trait for which a significant genetic influence is supported by multiple segregation analyses. Because genes associated with onset age may represent invaluable therapeutic targets to delay the disease, we sought to identify such genetic modifiers using a genomewide association study in familial PD. There have been previous genomewide association studies (GWAS) to identify genes influencing PD susceptibility, but this is the first to identify genes contributing to the variation in onset age.</p> <p>Methods</p> <p>Initial analyses were performed using genotypes generated with the Illumina HumanCNV370Duo array in a sample of 857 unrelated, familial PD cases. Subsequently, a meta-analysis of imputed SNPs was performed combining the familial PD data with that from a previous GWAS of 440 idiopathic PD cases. The SNPs from the meta-analysis with the lowest p-values and consistency in the direction of effect for onset age were then genotyped in a replication sample of 747 idiopathic PD cases from the Parkinson Institute Biobank of Milan, Italy.</p> <p>Results</p> <p>Meta-analysis across the three studies detected consistent association (p < 1 × 10<sup>-5</sup>) with five SNPs, none of which reached genomewide significance. On chromosome 11, the SNP with the lowest p-value (rs10767971; p = 5.4 × 10<sup>-7</sup>) lies between the genes <it>QSER1 </it>and <it>PRRG4</it>. Near the PARK3 linkage region on chromosome 2p13, association was observed with a SNP (rs7577851; p = 8.7 × 10<sup>-6</sup>) which lies in an intron of the <it>AAK1 </it>gene. This gene is closely related to <it>GAK</it>, identified as a possible PD susceptibility gene in the GWAS of the familial PD cases.</p> <p>Conclusion</p> <p>Taken together, these results suggest an influence of genes involved in endocytosis and lysosomal sorting in PD pathogenesis.</p
Mice lacking mitochondrial ferritin are more sensitive to doxorubicin-mediated cardiotoxicity
Peptide Receptor Radionuclide Therapy (PRRT) in a Patient Affected by Metastatic Breast Cancer with Neuroendocrine Differentiation
Murine in vitro cellular models to better understand adipogenesis and its potential applications
Adipogenesis has been extensively studied using in vitro models of cellular differentiation, enabling long-term regulation of fat cell metabolism in human adipose tissue (AT) material. Many studies promote the idea that manipulation of this process could potentially reduce the prevalence of obesity and its related diseases. It has now become essential to understand the molecular basis of fat cell development to tackle this pandemic disease, by identifying therapeutic targets and new biomarkers. This review explores murine cell models and their applications for study of the adipogenic differentiation process in vitro. We focus on the benefits and limitations of different cell line models to aid in interpreting data and selecting a good cell line model for successful understanding of adipose biology