ABSTRACT
OBJECTIVE: The Marfan syndrome (MFS) is an autosomal dominant disorder of connective tissue resulting from pathogenic variants of the fibrillin-1 gene (FBN1) with skeletal, cardiac, and ocular involvement. STUDY DESIGN: We report on a full-term male neonate, who showed at birth characteristics and dysmorphisms suggestive of nMFS, combined with the detection of severe cardiovascular disease. A multidisciplinary team made up of neonatologists and pediatricians, cardiologists, geneticists, ophtalmologists, physiatrists and physioterapists was formed to manage this patient. RESULTS AND CONCLUSION: Early diagnosis of this rare condition is critical for adequate treatment and specific follow-up, and impacts significantly on prognosis.
Subject(s)
Infant, Newborn, Diseases , Marfan Syndrome , Electrocardiography , Humans , Infant, Newborn , Male , Marfan Syndrome/genetics , Marfan Syndrome/surgery , Mitral Valve Prolapse/surgery , Mutation , Tricuspid Valve Prolapse/surgeryABSTRACT
Lipidomic analysis is able to measure simultaneously thousands of compounds belonging to a few lipid classes. In each lipid class, compounds differ only by the acyl radical, ranging between C10:0 (capric acid) and C24:0 (lignoceric acid). Although some metabolites have a peculiar pathological role, more often compounds belonging to a single lipid class exert the same biological effect. Here, we present a lipidomics workflow that extracts the tandem mass spectrometry data from individual files and uses them to group compounds into structurally homogeneous clusters by chemical structure hierarchical clustering analysis (CHCA). The case-to-control peak area ratios of the metabolites are then analyzed within clusters. We created two freely available applications to assist the workflow: FragClust to generate the tables to be subjected to CHCA, and TestClust to perform statistical analysis on clustered data. We used the lipidomics data from the plasma of Alzheimer's disease (AD) patients in comparison with healthy controls to test the workflow. To date, the search for plasma biomarkers in AD has not provided reliable results. This article shows that the workflow is helpful to understand the behavior of whole lipid classes in plasma of AD patients.
