Ferritin: A Biomarker Requiring Caution in Clinical Decision.

OBJECTIVES: To determine the ferritin inter-assay differences between three "Conformité Européenne" (CE) marked tests, the impact on reference intervals (RI), and the proportion of individuals with iron deficiency (ID), we used plasma and serum from healthy blood donors (HBD) recruited in three different Switzerland regions. DESIGN AND METHODS: Heparinized plasma and serum from HBD were obtained from three different transfusion centers in Switzerland (Fribourg, Geneva, and Neuchatel). One hundred forty samples were recruited per center and per matrix, with a gender ratio of 50%, for a total of 420 HBD samples available per matrix. On both matrices, ferritin concentrations were quantified by three different laboratories using electrochemiluminescence (ECL), latex immunoturbidimetric assay (LIA), and luminescent oxygen channeling immunoassay (LOCI) assays, respectively. The degree of agreement between matrices and between the three sites/methods was assessed by Passing-Bablok and we evaluated the proportion of individuals deemed to have ID per method. RESULTS: Overall, no difference between serum and heparinized plasma ferritin values was observed according to Passing-Bablok analyses (proportional bias range: 1.0-3.0%; maximum constant bias: 1.84 µg/L). Significant median ferritin differences (p < 0.001 according to Kruskal-Wallis test) were observed between the three methods (i.e., 83.6 µg/L, 103.5 µg/L, and 62.1 µg/L for ECL, LIA, and LOCI in heparinized plasma, respectively), with proportional bias varying significantly between ±16% and ±32% on serum and from ±14% to ±35% on plasma with no sign of gender-related differences. Affecting the lower end of RI, the proportion of ID per method substantially varied between 4.76% (20/420) for ECL, 2.86% (12/420) for LIA, and 9.05% (38/420) for LOCI. CONCLUSIONS: Serum and heparinized plasma are exchangeable for ferritin assessment. However, the order of magnitude of ferritin differences across methods and HBD recruitment sites could lead to diagnostic errors if uniform RI were considered. Challenging the recently proposed use of uniform ferritin thresholds, our results highlight the importance of method- and region-specific RI for ferritin due to insufficient inter-assay harmonization. Failing to do so significantly impacts ID diagnosis.

LC-MS (/MS) in clinical toxicology screening methods.

Toxicological screening is the analysis of biological samples to detect and identify unknown compounds. The high selectivity and sensitivity of liquid chromatography (LC) coupled to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) technology provide an attractive alternative to the current methods (LC-UV, GC/MS, etc.). For these reasons, an increasing number of applications are being published. This paper is a brief overview of LC-MS(/MS) screening methods developed for clinical toxicology in recent years. Various sample treatments, chromatographic separations and detection by mass spectrometry can be combined to obtain screening methods adapted to the constraints and needs of clinical toxicology laboratories. Currently the techniques are in the hands of specialists, mainly in academic institutions. However, the evolution in technology should allow application of these techniques as a tool in toxicology laboratories, thus allowing a more widespread exploitation of their potential.

Current role of liquid chromatography coupled to mass spectrometry in clinical toxicology screening methods.

Abstract Toxicological screening is the analysis of a biological specimen to detect and identify compounds in patients admitted to the hospital with acute intoxication of unknown origin. The screening of a wide range of toxicologically relevant compounds in biological samples is a serious challenge for clinical laboratories. The high selectivity and sensitivity of liquid chromatography coupled to mass spectrometry or tandem mass spectrometry technology provides an attractive alternative to the current methods. For these reasons, an increasing number of applications for multi-target screening or general screening of unknown compounds in biological matrices are being published. This paper is an overview of sample clean-up, chromatographic separation and mass spectrometry detection procedures which can be combined to obtain screening methods adapted to the constraints and needs of various laboratories, and none specifically in clinical toxicology. Currently the techniques are in the hands of specialists, principally in academic institutes. However, the evolution in technology should allow application of the techniques as a tool in toxicology laboratories and thus more widespread exploitation of their potential.

Characterization and classification of matrix effects in biological samples analyses.

An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.

X-Rank: a robust algorithm for small molecule identification using tandem mass spectrometry.

The diversity of experimental workflows involving LC-MS/MS and the extended range of mass spectrometers tend to produce extremely variable spectra. Variability reduces the accuracy of compound identification produced by commonly available software for a spectral library search. We introduce here a new algorithm that successfully matches MS/MS spectra generated by a range of instruments, acquired under different conditions. Our algorithm called X-Rank first sorts peak intensities of a spectrum and second establishes a correlation between two sorted spectra. X-Rank then computes the probability that a rank from an experimental spectrum matches a rank from a reference library spectrum. In a training step, characteristic parameter values are generated for a given data set. We compared the efficiency of the X-Rank algorithm with the dot-product algorithm implemented by MS Search from the National Institute of Standards and Technology (NIST) on two test sets produced with different instruments. Overall the X-Rank algorithm accurately discriminates correct from wrong matches and detects more correct substances than the MS Search. Furthermore, X-Rank could correctly identify and top rank eight chemical compounds in a commercially available test mix. This confirms the ability of the algorithm to perform both a straight single-platform identification and a cross-platform library search in comparison to other tools. It also opens the possibility for efficient general unknown screening (GUS) against large compound libraries.