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Articles by Hugo Vanderstichele
Total Records ( 3 ) for Hugo Vanderstichele
  Hugo Vanderstichele , Mirko Bibl , Sebastiaan Engelborghs , Nathalie Le Bastard , Piotr Lewczuk , Jose Luis Molinuevo , Lucilla Parnetti , Armand Perret- Liaudet , Leslie M. Shaw , Charlotte Teunissen , Dirk Wouters and Kaj Blennow
  Background Numerous studies show that the cerebrospinal fluid biomarkers total tau (T-tau), tau phosphorylated at threonine 181 (P-tau181P), and amyloid-β (1–42) (Aβ1–42) have high diagnostic accuracy for Alzheimer‘s disease. Variability in concentrations for Aβ1–42, T-tau, and P-tau181P drives the need for standardization. Methods Key issues were identified and discussed before the first meeting of the members of the Alzheimer‘s Biomarkers Standardization Initiative (ABSI). Subsequent ABSI consensus meetings focused on preanalytical issues. Results Consensus was reached on preanalytical issues such as the effects of fasting, different tube types, centrifugation, time and temperature before storage, storage temperature, repeated freeze/thaw cycles, and length of storage on concentrations of Aβ1–42, T-tau, and P-tau181P in cerebrospinal fluid. Conclusions The consensus reached on preanalytical issues and the recommendations put forward during the ABSI consensus meetings are presented in this paper.
  Michal J. Figurski , Teresa Waligorska , Jon Toledo , Hugo Vanderstichele , Magdalena Korecka , Virginia M.Y. Lee , John Q. Trojanowski and Leslie M. Shaw
  Background The interassay variability and inconsistency of plasma β-amyloid (Aβ) measurements among centers are major factors precluding the interpretation of results and a substantial obstacle in the meta-analysis across studies of this biomarker. The goal of this investigation was to address these problems by improving the performance of the bioanalytical method. Methods We used the Luminex immunoassay platform with a multiplex microsphere-based reagent kit from Innogenetics. A robotic pipetting system was used to perform crucial steps of the procedure. The performance of this method was evaluated using two kit control samples and two quality control plasma samples from volunteer donors, and by retesting previously assayed patient samples in each run. This setup was applied to process 2454 patient plasma samples from the Alzheimer‘s Disease Neuroimaging Initiative study biofluid repository. We have additionally evaluated the correlations between our results and cerebrospinal fluid (CSF) biomarker data using mixed-effects modeling. Results The average precision values of the kit controls were 8.3% for Aβ1-40 and 4.0% for Aβ1-42, whereas the values for the plasma quality controls were 6.4% for Aβ1-40 and 4.8% for Aβ1-42. From the test–retest evaluation, the average precision was 7.2% for Aβ1-40 and 4.5% for Aβ1-42. The range of final plasma results for Alzheimer‘s Disease Neuroimaging Initiative patients was 13 to 372 pg/mL (median: 164 pg/mL) for Aβ1-40 and 3.5 to 103 pg/mL (median: 39.3 pg/mL) for Aβ1-42. We found that sample collection parameters (blood volume and time to freeze) have a small, but significant, influence on the result. No significant difference was found between plasma Aβ levels for patients with Alzheimer‘s disease and healthy control subjects. We have determined multiple significant correlations of plasma Aβ1-42 levels with CSF biomarkers. The relatively strongest, although modest, correlation was found between plasma Aβ1-42 levels and CSF p-tau181/Aβ1-42 ratio in patients with mild cognitive impairment. Plasma Aβ1-40 correlations with CSF biomarkers were weaker and diminished completely when we used longitudinal data. No significant correlations were found for the plasma Aβ1-42/Aβ1-40 ratio. Conclusions The precision of our robotized method represents a substantial improvement over results reported in the literature. Multiple significant correlations between plasma and CSF biomarkers were found. Although these correlations are not strong enough to support the use of plasma Aβ measurement as a diagnostic screening test, plasma Aβ1-42 levels are well suited for use as a pharmacodynamic marker.
  Niklas Mattsson , Ulf Andreasson , Staffan Persson , Maria C. Carrillo , Steven Collins , Sonia Chalbot , Neal Cutler , Diane Dufour- Rainfray , Anne M. Fagan , Niels H.H. Heegaard , Ging-Yuek Robin Hsiung , Bradley Hyman , Khalid Iqbal , D. Richard Lachno , Alberto Lleo , Piotr Lewczuk , Jose L. Molinuevo , Piero Parchi , Axel Regeniter , Robert Rissman , Hanna Rosenmann , Giuseppe Sancesario , Johannes Schroder , Leslie M. Shaw , Charlotte E. Teunissen , John Q. Trojanowski , Hugo Vanderstichele , Manu Vandijck , Marcel M. Verbeek , Henrik Zetterberg , Kaj Blennow and Stephan A. Kaser
  Background The cerebrospinal fluid (CSF) biomarkers amyloid beta 1–42, total tau, and phosphorylated tau are used increasingly for Alzheimer's disease (AD) research and patient management. However, there are large variations in biomarker measurements among and within laboratories. Methods Data from the first nine rounds of the Alzheimer's Association quality control program was used to define the extent and sources of analytical variability. In each round, three CSF samples prepared at the Clinical Neurochemistry Laboratory (Molndal, Sweden) were analyzed by single-analyte enzyme-linked immunosorbent assay (ELISA), a multiplexing xMAP assay, or an immunoassay with electrochemoluminescence detection. Results A total of 84 laboratories participated. Coefficients of variation (CVs) between laboratories were around 20% to 30%; within-run CVs, less than 5% to 10%; and longitudinal within-laboratory CVs, 5% to 19%. Interestingly, longitudinal within-laboratory CV differed between biomarkers at individual laboratories, suggesting that a component of it was assay dependent. Variability between kit lots and between laboratories both had a major influence on amyloid beta 1–42 measurements, but for total tau and phosphorylated tau, between-kit lot effects were much less than between-laboratory effects. Despite the measurement variability, the between-laboratory consistency in classification of samples (using prehoc-derived cutoffs for AD) was high (>90% in 15 of 18 samples for ELISA and in 12 of 18 samples for xMAP). Conclusions The overall variability remains too high to allow assignment of universal biomarker cutoff values for a specific intended use. Each laboratory must ensure longitudinal stability in its measurements and use internally qualified cutoff levels. Further standardization of laboratory procedures and improvement of kit performance will likely increase the usefulness of CSF AD biomarkers for researchers and clinicians.
 
 
 
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