Paving the Way to Precision Nutrition Through Metabolomics

Nutrition is an interdisciplinary science that studies the interactions of nutrients with the body in relation to maintenance of health and well-being. Nutrition is highly complex due to the underlying various internal and external factors that could model it. Thus, hacking this complexity requires more holistic and network-based strategies that could unveil these dynamic system interactions at both time and space scales. The ongoing omics era with its high-throughput molecular data generation is paving the way to embrace this complexity and is deeply reshaping the whole field of nutrition. Understanding the future paths of nutrition science is of importance from both translational and clinical perspectives. Basic nutrients which might include metabolites are important in nutrition science. Moreover, metabolites are key biological communication channels and represent an appealing functional readout at the interface of different major influential factors that define health and disease. Metabolomics is the technology that enables holistic and systematic analyses of metabolites in a biological system. Hence, given its intrinsic functionality, its tight connection to metabolism and its high clinical actionability potential, metabolomics is a very appealing technology for nutrition science. The ultimate goal is to deliver a tailored and clinically relevant nutritional recommendations and interventions to achieve precision nutrition. This work intends to present an update on the applications of metabolomics to personalize nutrition in translational and clinical settings. It also discusses the current conceptual shifts that are remodeling clinical nutrition practices in this Precision Medicine era. Finally, perspectives of clinical nutrition in the ever-growing, data-driven healthcare landscape are presented

Integration of molecular profiles in a longitudinal wellness profiling cohort

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine

The human secretome

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood

Multidimensional metabolomics analysis : application to Inborn Errors of Metabolism

La médecine de précision (MP) est un nouveau paradigme qui révolutionne la pratique médicale actuelle et remodèle complètement la médecine de demain. La MP aspire à placer le patient au centre du parcours de soins en y intégrant les données médicales et biologiques individuelles tout en tenant compte de la grande diversité interindividuelle. La prédiction des états pathologiques chez les patients nécessite une compréhension dynamique et systémique. Les erreurs innées du métabolisme (EIM) sont des troubles génétiques résultant de défauts dans une voie biochimique donnée en raison de la déficience d'une enzyme, de son cofacteur ou d’un transporteur. Les EIM ne sont plus considérées comme des maladies monogéniques mais tendent à être plus complexes et multifactorielles. Le profil métabolomique permet le dépistage d’une pathologie, la recherche de biomarqueurs et l’exploration des voies métaboliques mises en jeu. Dans ce travail de thèse, nous avons utilisé l’approche métabolomique qui est particulièrement pertinente pour les EIM compte tenu de leur physiopathologie de base qui est étroitement liée au métabolisme. Ce travail a permis la mise en place d’une méthodologie métabolomique non ciblée basée sur une stratégie analytique multidimensionnelle comportant la spectrométrie de masse à haute résolution couplée à la chromatographie liquide ultra-haute performance et la mobilité ionique. La mise en place de la méthodologie de prétraitement, d’analyse et d’exploitation des données générées avec des outils de design expérimental et d’analyses multivariées ont été aussi établies. Enfin, cette approche a été appliquée pour l’exploration des EIM avec les mucopolysaccharidoses comme preuve de concept. Les résultats obtenus suggèrent un remodelage majeur du métabolisme des acides aminés dans la mucopolysaccharidose de type I. En résumé, la métabolomique pourrait être un outil complémentaire pertinent en appui à l’approche génomique dans l’exploration des EIM.The new field of precision medicine is revolutionizing current medical practice and reshaping future medicine. Precision medicine intends to put the patient as the central driver of healthcare by broadening biological knowledge and acknowledging the great diversity of individuals. The prediction of physiological and pathological states in patients requires a dynamic and systemic understanding of these interactions. Inborn errors of metabolism (IEM) are genetic disorders resulting from defects in a given biochemical pathway due to the deficiency of an enzyme, its cofactor or a transporter. IEM are no longer considered to be monogenic diseases, which adds another layer of complexity to their characterization and diagnosis. To meet this need for faster screening, the metabolic profile can be a promising candidate given its ability in disease screening, biomarker discovery and metabolic pathway investigation. In this thesis, we used a metabolomic approach which is particularly relevant for IEM given their basic pathophysiology that is tightly related to metabolism. This thesis allowed the implementation of an untargeted metabolomic methodology based on a multidimensional analytical strategy including high-resolution mass spectrometry coupled with ultra-high-performance liquid chromatography and ion mobility. This work also set a methodology for preprocessing, analysis and interpretation of the generated data using experimental design and multivariate data analysis. Finally, the strategy is applied to the exploration of IEM with mucopolysaccharidoses as a proof of concept. The results suggest a major remodeling of the amino acid metabolisms in mucopolysaccharidosis type I. In summary, metabolomic is a relevant complementary tool to support the genomic approach in the functional investigations and diagnosis of IEM

Analyse métabolomique multidimensionnelle : applications aux erreurs innées du métabolisme

The new field of precision medicine is revolutionizing current medical practice and reshaping future medicine. Precision medicine intends to put the patient as the central driver of healthcare by broadening biological knowledge and acknowledging the great diversity of individuals. The prediction of physiological and pathological states in patients requires a dynamic and systemic understanding of these interactions. Inborn errors of metabolism (IEM) are genetic disorders resulting from defects in a given biochemical pathway due to the deficiency of an enzyme, its cofactor or a transporter. IEM are no longer considered to be monogenic diseases, which adds another layer of complexity to their characterization and diagnosis. To meet this need for faster screening, the metabolic profile can be a promising candidate given its ability in disease screening, biomarker discovery and metabolic pathway investigation. In this thesis, we used a metabolomic approach which is particularly relevant for IEM given their basic pathophysiology that is tightly related to metabolism. This thesis allowed the implementation of an untargeted metabolomic methodology based on a multidimensional analytical strategy including high-resolution mass spectrometry coupled with ultra-high-performance liquid chromatography and ion mobility. This work also set a methodology for preprocessing, analysis and interpretation of the generated data using experimental design and multivariate data analysis. Finally, the strategy is applied to the exploration of IEM with mucopolysaccharidoses as a proof of concept. The results suggest a major remodeling of the amino acid metabolisms in mucopolysaccharidosis type I. In summary, metabolomic is a relevant complementary tool to support the genomic approach in the functional investigations and diagnosis of IEM.La médecine de précision (MP) est un nouveau paradigme qui révolutionne la pratique médicale actuelle et remodèle complètement la médecine de demain. La MP aspire à placer le patient au centre du parcours de soins en y intégrant les données médicales et biologiques individuelles tout en tenant compte de la grande diversité interindividuelle. La prédiction des états pathologiques chez les patients nécessite une compréhension dynamique et systémique. Les erreurs innées du métabolisme (EIM) sont des troubles génétiques résultant de défauts dans une voie biochimique donnée en raison de la déficience d'une enzyme, de son cofacteur ou d’un transporteur. Les EIM ne sont plus considérées comme des maladies monogéniques mais tendent à être plus complexes et multifactorielles. Le profil métabolomique permet le dépistage d’une pathologie, la recherche de biomarqueurs et l’exploration des voies métaboliques mises en jeu. Dans ce travail de thèse, nous avons utilisé l’approche métabolomique qui est particulièrement pertinente pour les EIM compte tenu de leur physiopathologie de base qui est étroitement liée au métabolisme. Ce travail a permis la mise en place d’une méthodologie métabolomique non ciblée basée sur une stratégie analytique multidimensionnelle comportant la spectrométrie de masse à haute résolution couplée à la chromatographie liquide ultra-haute performance et la mobilité ionique. La mise en place de la méthodologie de prétraitement, d’analyse et d’exploitation des données générées avec des outils de design expérimental et d’analyses multivariées ont été aussi établies. Enfin, cette approche a été appliquée pour l’exploration des EIM avec les mucopolysaccharidoses comme preuve de concept. Les résultats obtenus suggèrent un remodelage majeur du métabolisme des acides aminés dans la mucopolysaccharidose de type I. En résumé, la métabolomique pourrait être un outil complémentaire pertinent en appui à l’approche génomique dans l’exploration des EIM

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

International audienc

Intraventricular Hemorrhage in Very Preterm Infants: A Comprehensive Review

Germinal matrix-intraventricular-intraparenchymal hemorrhage (GMH-IVH-IPH) is a major complication of very preterm births before 32 weeks of gestation (WG). Despite progress in clinical management, its incidence remains high before 27 WG. In addition, severe complications may occur such as post-hemorrhagic hydrocephalus and/or periventricular intraparenchymal hemorrhage. IVH is strongly associated with subsequent neurodevelopmental disabilities. For this review, an automated literature search and a clustering approach were applied to allow efficient filtering as well as topic clusters identification. We used a programmatic literature search for research articles related to intraventricular hemorrhage in preterms that were published between January 1990 and February 2020. Two queries ((Intraventricular hemorrhage) AND (preterm)) were used in PubMed. This search resulted in 1093 articles. The data manual curation left 368 documents that formed 12 clusters. The presentation and discussion of the clusters provide a comprehensive overview of existing data on the pathogenesis, complications, neuroprotection and biomarkers of GMH-IVH-IPH in very preterm infants. Clinicians should consider that the GMH-IVH-IPH pathogenesis is mainly due to developmental immaturity of the germinal matrix and cerebral autoregulation impairment. New multiomics investigations of intraventricular hemorrhage could foster the development of predictive biomarkers for the benefit of very preterm newborns

Precision Neurosurgery: A Path Forward

Since the inception of their profession, neurosurgeons have defined themselves as physicians with a surgical practice. Throughout time, neurosurgery has always taken advantage of technological advances to provide better and safer care for patients. In the ongoing precision medicine surge that drives patient-centric healthcare, neurosurgery strives to effectively embrace the era of data-driven medicine. Neuro-oncology best illustrates this convergence between surgery and precision medicine with the advent of molecular profiling, imaging and data analytics. This convenient convergence paves the way for new preventive, diagnostic, prognostic and targeted therapeutic perspectives. The prominent advances in healthcare and big data forcefully challenge the medical community to deeply rethink current and future medical practice. This work provides a historical perspective on neurosurgery. It also discusses the impact of the conceptual shift of precision medicine on neurosurgery through the lens of neuro-oncology

Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era

International audienc

Acute Respiratory Infection Unveiling CPT II Deficiency

Carnitine Palmitoyl transferase 2 (CPT II) is involved in long-chain fatty-acid mitochondrial transport. Three clinical phenotypes of CPT II deficiency have been described: Lethal neonatal onset, infantile severe form, and the late onset more common muscular form. The muscular form of CPT II deficiency is characterized by pain crises and rhabdomyolysis triggered by energy-dependent factors. This form has been described as a benign condition; however, the acute crises are insidious and thus, pose a risk of death. We report a 3-year-old female child with an acute pulmonary infection and a concomitant rhabdomyolysis. The acylcarnitine profile was consistent with CPT II deficiency and a molecular study allowed the identification of the common missense variant (NM_000098.2: c.338C>T – p. Ser113Leu) at the homozygous state. The striking difference between the initial cause and the decompensation severity prompted us to consider other diagnoses. Deciphering the symptoms linked to CPT II deficiency among those of the initial decompensation results in initiating a timely a targeted therapy