Molecular allergology: a clinical laboratory tool for precision diagnosis, stratification and follow-up of allergic patients.

Identification of the molecular culprits of allergic reactions leveraged molecular allergology applications in clinical laboratory medicine. Molecular allergology shifted the focus from complex, heterogeneous allergenic extracts, e.g. pollen, food, or insect venom, towards genetically and immunologically defined proteins available for in vitro diagnosis. Molecular allergology is a precision medicine approach for the diagnosis, stratification, therapeutic management, follow-up and prognostic evaluation of patients within a large range of allergic diseases. Exclusively available for in vitro diagnosis, molecular allergology is nonredundant with any of the current clinical tools for allergy investigation. As an example of a major application, discrimination of genuine sensitization from allergen cross-reactivity at the molecular level allows the proper targeting of the culprit allergen and thus dramatically improves patient management. This review aims at introducing clinical laboratory specialists to molecular allergology, from the biochemical and genetic bases, through immunological concepts, to daily use in the diagnosis and management of allergic diseases.

Characterization of the novel HLA-B*15:648 allele by next-generation sequencing.

HLA-B*15:648 differs from HLA-B*15:02:01:01 by one nucleotide substitution in codon 77 in exon 2.

Characterisation of the novel HLA-DQA1*04:14N allele by next-generation sequencing.

HLA-DQA1*04:14N differs from HLA-DQA1*04:01:01:03 by a single nucleotide deletion in codon 113 in exon 3.

Characterization of the novel HLA-A*01:383 allele by next-generation sequencing.

HLA-A*01:383 differs from HLA-A*01:01:01:01 by two nucleotide substitutions at positions 28 and 48 in exon 1.

Characterization of the novel HLA-A*33:220 allele by next-generation sequencing.

HLA-A*33:220 differs from HLA-A*33:03:01:01 by one nucleotide substitution in codon 245 in exon 4.

Characterization of the novel HLA-C*07:1001N allele by next-generation sequencing.

HLA-C*07:1001N differs from HLA-C*07:01:01:01 by a deletion of 17 nucleotides in exon 1.

Characterization of the novel HLA-C*16:184 allele by next-generation sequencing.

HLA-C*16:184 differs from HLA-C*16:02:01:01 by one nucleotide substitution at position 737 in exon 3.

Characterization of the novel HLA-C*03:04:94 allele by next-generation sequencing.

HLA-C*03:04:94 differs from HLA-C*03:04:01:01 by one nucleotide substitution at position 737 in exon 4.

Characterization of the novel HLA-C*05:255 allele by next-generation sequencing.

HLA-C*05:255 differs from HLA-C*05:01:01:02 by one nucleotide substitution at position 2013 in exon 5.

Characterization of the novel HLA-B*53:64 allele by next-generation sequencing.

HLA-B*53:64 differs from HLA-B*53:01:01:01 by one nucleotide substitution at position 1617 in exon 4.

Characterization of the novel HLA-C*06:317 allele by next-generation sequencing.

HLA-C*06:317 differs from HLA-C*06:02:01:01 by one nucleotide substitution at position 921 in exon 3.

External Evaluation of Population Pharmacokinetic Models and Bayes-Based Dosing of Infliximab.

Despite the well-demonstrated efficacy of infliximab in inflammatory diseases, treatment failure remains frequent. Dose adjustment using Bayesian methods has shown in silico its interest in achieving target plasma concentrations. However, most of the published models have not been fully validated in accordance with the recommendations. This study aimed to submit these models to an external evaluation and verify their predictive capabilities. Eight models were selected for external evaluation, carried out on an independent database (409 concentrations from 157 patients). Each model was evaluated based on the following parameters: goodness-of-fit (comparison of predictions to observations), residual error model (population weighted residuals (PWRES), individual weighted residuals (IWRES), and normalized prediction distribution errors (NPDE)), and predictive performances (prediction-corrected visual predictive checks (pcVPC) and Bayesian simulations). The performances observed during this external evaluation varied greatly from one model to another. The eight evaluated models showed a significant bias in population predictions (from -7.19 to 7.38 mg/L). Individual predictions showed acceptable bias and precision for six of the eight models (mean error of -0.74 to -0.29 mg/L and mean percent error of -16.6 to -0.4%). Analysis of NPDE and pcVPC confirmed these results and revealed a problem with the inclusion of several covariates (weight, concomitant immunomodulatory treatment, presence of anti-drug antibodies). This external evaluation showed satisfactory results for some models, notably models A and B, and highlighted several prospects for improving the pharmacokinetic models of infliximab for clinical-biological application.

Absence of Anti-Glomerular Basement Membrane Antibodies in 200 Patients With Systemic Lupus Erythematosus With or Without Lupus Nephritis: Results of the GOODLUPUS Study.

Introduction: Anti-glomerular basement membrane (GBM) antibodies are pathogenic antibodies first detected in renal-limited anti-GBM disease and in Goodpasture disease, the latter characterized by rapidly progressive crescentic glomerulonephritis combined with intra-alveolar hemorrhage. Studies have suggested that anti-GBM antibody positivity may be of interest in lupus nephritis (LN). Moreover, severe anti-GBM vasculitis cases in patients with systemic lupus erythematosus (SLE) have been described in the literature, but few studies have assessed the incidence of anti-GBM antibodies in SLE patients. Objective: The main study objective was to determine if positive anti-GBM antibodies were present in the serum of SLE patients with or without proliferative renal damage and compared to a healthy control group. Methodology: This retrospective study was performed on SLE patients' sera from a Franco-German European biobank, developed between 2011 and 2014, from 17 hospital centers in the Haut-Rhin region. Patients were selected according to their renal involvement, and matched by age and gender. The serum from healthy voluntary blood donors was also tested. Anti-GBM were screened by fluorescence enzyme immunoassay (FEIA), and then by indirect immunofluorescence (IIF) in case of low reactivity detection (titer >6 U/ml). Results: The cohort was composed of 100 SLE patients with proliferative LN (27% with class III, 67% with class IV, and 6% with class V), compared to 100 SLE patients without LN and 100 controls. Patients were mostly Caucasian and met the ACR 1997 criteria and/or the SLICC 2012 criteria. Among the 300 tested sera, no significant levels of anti-GBM antibodies were detected (>10 U/ml) by the automated technique, three sera were found "ambivalent" (>7 U/ml): one in the SLE with LN group and two in the SLE without LN group. Subsequent IIF assays did not detect anti-GBM antibodies. Conclusion: Anti-GBM antibodies were not detected in the serum of Caucasian patients with SLE, even in case of renal involvement, a situation favoring the antigenic exposure of glomerular basement membranes. Our results reaffirm the central role of anti-GBM antibodies as a specific diagnostic biomarker for Goodpasture vasculitis and therefore confirm that anti-GBM antibody must not be carried out in patients with SLE (with or without LN) in the absence of disease-suggestive symptoms.