Utility of Gene Panels for the Diagnosis of Inborn Errors of Metabolism in a Metabolic Reference Center

Next-generation sequencing (NGS) technologies have been proposed as a first-line test for the diagnosis of inborn errors of metabolism (IEM), a group of genetically heterogeneous disorders with overlapping or nonspecific phenotypes. Over a 3-year period, we prospectively analyzed 311 pediatric patients with a suspected IEM using four targeted gene panels. The rate of positive diagnosis was 61.86% for intermediary metabolism defects, 32.84% for complex molecular defects, 19% for hypoglycemic/hyperglycemic events, and 17% for mitochondrial diseases, and a conclusive molecular diagnosis was established in 2-4 weeks. Forty-one patients for whom negative results were obtained with the mitochondrial diseases panel underwent subsequent analyses using the NeuroSeq panel, which groups all genes from the individual panels together with genes associated with neurological disorders (1870 genes in total). This achieved a diagnostic rate of 32%. We next evaluated the utility of a tool, Phenomizer, for differential diagnosis, and established a correlation between phenotype and molecular findings in 39.3% of patients. Finally, we evaluated the mutational architecture of the genes analyzed by determining z-scores, loss-of-function observed/expected upper bound fraction (LOEUF), and haploinsufficiency (HI) scores. In summary, targeted gene panels for specific groups of IEMs enabled rapid and effective diagnosis, which is critical for the therapeutic management of IEM patients.info:eu-repo/semantics/publishedVersio

Reconstruction of Longitudinal Profiles of Ultra-High Energy Cosmic Ray Showers from Fluorescence and Cherenkov Light Measurements

We present a new method for the reconstruction of the longitudinal profile of extensive air showers induced by ultra-high energy cosmic rays. In contrast to the typically considered shower size profile, this method employs directly the ionization energy deposit of the shower particles in the atmosphere. Due to universality of the energy spectra of electrons and positrons, both fluorescence and Cherenkov light can be used simultaneously as signal to infer the shower profile from the detected light. The method is based on an analytic least-square solution for the estimation of the shower profile from the observed light signal. Furthermore, the extrapolation of the observed part of the profile with a Gaisser-Hillas function is discussed and the total statistical uncertainty of shower parameters like total energy and shower maximum is calculated.Comment: accepted by NIM