Use of dried blood spots for monitoring inflammatory and nutritional biomarkers in the elderly.

OBJECTIVES: Blood microsampling, particularly dried blood spots (DBSs), is an attractive minimally-invasive approach that is well suited for home sampling and predictive medicine associated with longitudinal follow-up of the elderly. However, in vitro diagnostic quantification of biomarkers from DBS poses a major challenge. Clinical mass spectrometry can reliably quantify blood proteins in various research projects. Our goal here was to use mass spectrometry of DBS in a real-world clinical setting and compared it to the standard immunoassay method. We also sought to correlate DBS mass spectrometry measurements with clinical indices. METHODS: A clinical trial of diagnostic equivalence was conducted to compare conventional venous samples quantified by immunoassay and DBSs quantified by mass spectrometry in an elderly population. We assayed three protein biomarkers of nutritional and inflammatory status: prealbumin (transthyretin), C-reactive protein, and transferrin. RESULTS: The analysis of DBSs showed satisfactory variability and low detection limits. Statistical analysis confirmed that the two methods give comparable results at clinical levels of accuracy. In conclusion, we demonstrated, in a real-life setting, that DBSs can be used to measure prealbumin, CRP and transferrin, which are commonly used markers of nutritional status and inflammation in the elderly. However, there was no correlation with patient frailty for these proteins. CONCLUSIONS: Early detection and regular monitoring of nutritional and inflammatory problems using DBS appear to be clinically feasible. This could help resolve major public health challenges in the elderly for whom frailty leads to serious risks of health complications.

New Perspectives of Multiplex Mass Spectrometry Blood Protein Quantification on Microsamples in Biological Monitoring of Elderly Patients.

Blood microsampling combined with large panels of clinically relevant tests are of major interest for the development of home sampling and predictive medicine. The aim of the study was to demonstrate the practicality and medical utility of microsamples quantification using mass spectrometry (MS) in a clinical setting by comparing two types of microsamples for multiplex MS protein detection. In a clinical trial based on elderly population, we compared 2 µL of plasma to dried blood spot (DBS) with a clinical quantitative multiplex MS approach. The analysis of the microsamples allowed the quantification of 62 proteins with satisfactory analytical performances. A total of 48 proteins were significantly correlated between microsampling plasma and DBS (p < 0.0001). The quantification of 62 blood proteins allowed us to stratify patients according to their pathophysiological status. Apolipoproteins D and E were the best biomarker link to IADL (instrumental activities of daily living) score in microsampling plasma as well as in DBS. It is, thus, possible to detect multiple blood proteins from micro-samples in compliance with clinical requirements and this allows, for example, to monitor the nutritional or inflammatory status of patients. The implementation of this type of analysis opens new perspectives in the field of diagnosis, monitoring and risk assessment for personalized medicine approaches.

Serum neurofilament light chain cut-off definition for clinical diagnosis and prognosis of amyotrophic lateral sclerosis.

BACKGROUND: The neurofilament light chain (NfL) assay is gradually becoming an essential diagnostic tool for the diagnosis of many neurological diseases including amyotrophic lateral sclerosis (ALS). Different methods for the determination of this biomarker in serum have been developed in recent years. METHODS: We measured blood NfL in 429 patients referred to the tertiary ALS center of Montpellier, France using two different ultrasensitive methods (Ella™ and Simoa™) and we compared the clinical performances of these two approaches. We also converted NfL values into age and body mass index-adjusted Z-scores to assess cut-off values of this biomarker in this clinical context. RESULTS: We show comparable diagnostic and prognostic performance of Ella™ and Simoa™ technologies in ALS, with specificities and sensitivities exceeding 80% for both. We propose cut-off values for serum NfL in this clinical context, thus enabling the routine clinical use of this biomarker. CONCLUSION: The use of NfL in routine clinical practice will help predict survival and improve diagnostic accuracy by distinguishing ALS from other neurological diseases and motor neuron disease mimics.

ifCNV: A novel isolation-forest-based package to detect copy-number variations from various targeted NGS datasets.

Copy-number variations (CNVs) are an essential component of genetic variation distributed across large parts of the human genome. CNV detection from next-generation sequencing data and artificial intelligence algorithms have progressed in recent years. However, only a few tools have taken advantage of machine-learning algorithms for CNV detection, and none propose using artificial intelligence to automatically detect probable CNV-positive samples. The most developed approach is to use a reference or normal dataset to compare with the samples of interest, and it is well known that selecting appropriate normal samples represents a challenging task that dramatically influences the precision of results in all CNV-detecting tools. With careful consideration of these issues, we propose here ifCNV, a new software based on isolation forests that creates its own reference, available in R and python with customizable parameters. ifCNV combines artificial intelligence using two isolation forests and a comprehensive scoring method to faithfully detect CNVs among various samples. It was validated using targeted next-generation sequencing (NGS) datasets from diverse origins (capture and amplicon, germline and somatic), and it exhibits high sensitivity, specificity, and accuracy. ifCNV is a publicly available open-source software (https://github.com/SimCab-CHU/ifCNV) that allows the detection of CNVs in many clinical situations.

Optimization of Patient Management in the Gynecology Emergency Department Using Point-of-Care Beta hCG.

Background: Point-of-care testing (POCT) provides shorter turn-around times and, in many cases, potentially improves medical decision making. The AQT90 FLEX® benchtop immunoanalyzer (Radiometer Medical ApS, Copenhagen, Denmark) allows for the determination of beta-human chorionic gonadotropin (ßhCG) in 18 min. The main aim of this study was to evaluate the impact of measuring ßhCG using the AQT90 analyzer in the gynecology emergency department (ED) compared to the standard practice of using central laboratory blood testing on the patient length of stay (LOS). Methods: The evaluation consisted of two parts. The first one, conducted in the central laboratory, focused on the analytical performances of the AQT ßhCG assay. The second one, conducted in the ED, aimed at determining the impact of POCT ßhCG implementation on the timeframe in which ED patients require ßhCG assessment. Results: The within-lab imprecisions at the mean values of 17 and 287 IU/L were 2.7% and 3.7%, respectively. Using Deming regression (n = 60), the following equation was obtained in the central lab: AQT90 ßhCG = 1.1 Roche ßhCG­12.9 (r = 0.997). The implementation of POCT ßhCG in the ED significantly reduced patient LOS (145 (90−212) min vs. 205 (155−265) with and without AQT90, respectively, p < 0.001). At the 2 IU/L decision level, a 99.7% agreement with the Roche assay was reported (kappa statistics, 0.99). Conclusions: We confirm that the analytical qualities of the AQT 90 were in line with those obtained in the central lab. The implementation of the POCT ßhCG is associated with a shorter LOS in the ED due to the faster availability of the results and the faster decision-making possibilities.