Higher precision, first tier newborn screening for metachromatic leukodystrophy using 16:1-OH-sulfatide.

Newborn screening (NBS) for metachromatic leukodystrophy (MLD) is based on first-tier measurement of sulfatides in dried blood spots (DBS) followed by second-tier measurement of arylsulfatase A in the same DBS. This approach is very precise with 0-1 false positives per ∼30,000 newborns tested. Recent data reported here shows that the sulfatide molecular species with an α-hydroxyl, 16­carbon, mono-unsaturated fatty acyl group (16:1-OH-sulfatide) is superior to the original biomarker 16:0-sulfatide in reducing the number of first-tier false positives. This result is consistent across 4 MLD NBS centers. By measuring 16:1-OH-sulfatide alone or together with 16:0-sulfatide, the estimated false positive rate is 0.048% and is reduced essentially to zero with second-tier arylsulfatase A activity assay. The false negative rate is predicted to be extremely low based on the demonstration that 40 out of 40 newborn DBS from clinically-confirmed MLD patients are detected with these methods. The work shows that NBS for MLD is extremely precise and ready for deployment. Furthermore, it can be multiplexed with several other inborn errors of metabolism already tested in NBS centers worldwide.

New insights and potential biomarkers for intraventricular hemorrhage in extremely premature infant, case-control study.

BACKGROUND: Despite advancements in neonatal care, germinal matrix-intraventricular hemorrhage impacts 20% of very preterm infants, exacerbating their neurological prognosis. Understanding its complex, multifactorial pathophysiology and rapid onset remains challenging. This study aims to link specific cord blood biomolecules at birth with post-natal germinal matrix-intraventricular hemorrhage onset. METHODS: A monocentric, prospective case-control study was conducted at Rouen University Hospital from 2015 to 2020. Premature newborns ( < 30 gestational age) were included and cord blood was sampled in the delivery room. A retrospective matching procedure was held in 2021 to select samples for proteomic and metabolomic analysis of 370 biomolecules. RESULTS: 26 patients with germinal matrix-intraventricular hemorrhage cases and 60 controls were included. Clinical differences were minimal, except for higher invasive ventilation rates in the germinal matrix-intraventricular hemorrhage group. Germinal matrix-intraventricular hemorrhage newborns exhibited lower phosphatidylcholine levels and elevated levels of four proteins: BOC cell adhesion-associated protein, placental growth factor, Leukocyte-associated immunoglobulin-like receptor 2, and tumor necrosis factor-related apoptosis-inducing ligand receptor 2. CONCLUSION: This study identifies biomolecules that may be linked to subsequent germinal matrix-intraventricular hemorrhage, suggesting heightened vascular disruption risk as an independent factor. These results need further validation but could serve as early germinal matrix-intraventricular hemorrhage risk biomarkers for future evaluations. IMPACT: Decrease in certain phosphatidylcholines and increase in four proteins in cord blood at birth may be linked to subsequent germinal matrix-intraventricular hemorrhage in premature newborns. The four proteins are BOC cell adhesion-associated protein, placental growth factor, leukocyte-associated immunoglobulin-like receptor 2, and TNF-related apoptosis-inducing ligand receptor 2. This biological imprint could point toward higher vascular disruption risk as an independent risk factor for this complication and with further validations, could be used for better stratification of premature newborns at birth.

Disentangling molecular and clinical stratification patterns in beta-galactosidase deficiency.

INTRODUCTION: This study aims to define the phenotypic and molecular spectrum of the two clinical forms of ß-galactosidase (ß-GAL) deficiency, GM1-gangliosidosis and mucopolysaccharidosis IVB (Morquio disease type B, MPSIVB). METHODS: Clinical and genetic data of 52 probands, 47 patients with GM1-gangliosidosis and 5 patients with MPSIVB were analysed. RESULTS: The clinical presentations in patients with GM1-gangliosidosis are consistent with a phenotypic continuum ranging from a severe antenatal form with hydrops fetalis to an adult form with an extrapyramidal syndrome. Molecular studies evidenced 47 variants located throughout the sequence of the GLB1 gene, in all exons except 7, 11 and 12. Eighteen novel variants (15 substitutions and 3 deletions) were identified. Several variants were linked specifically to early-onset GM1-gangliosidosis, late-onset GM1-gangliosidosis or MPSIVB phenotypes. This integrative molecular and clinical stratification suggests a variant-driven patient assignment to a given clinical and severity group. CONCLUSION: This study reports one of the largest series of b-GAL deficiency with an integrative patient stratification combining molecular and clinical features. This work contributes to expand the community knowledge regarding the molecular and clinical landscapes of b-GAL deficiency for a better patient management.

iNetModels 2.0: an interactive visualization and database of multi-omics data.

It is essential to reveal the associations between various omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics, plasma metabolomics, as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and disease research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.

Blood protein profiles related to preterm birth and retinopathy of prematurity.

BACKGROUND: Nearly one in ten children is born preterm. The degree of immaturity is a determinant of the infant's health. Extremely preterm infants have higher morbidity and mortality than term infants. One disease affecting extremely preterm infants is retinopathy of prematurity (ROP), a multifactorial neurovascular disease that can lead to retinal detachment and blindness. The advances in omics technology have opened up possibilities to study protein expressions thoroughly with clinical accuracy, here used to increase the understanding of protein expression in relation to immaturity and ROP. METHODS: Longitudinal serum protein profiles the first months after birth in 14 extremely preterm infants were integrated with perinatal and ROP data. In total, 448 unique protein targets were analyzed using Proximity Extension Assays. RESULTS: We found 20 serum proteins associated with gestational age and/or ROP functioning within mainly angiogenesis, hematopoiesis, bone regulation, immune function, and lipid metabolism. Infants with severe ROP had persistent lower levels of several identified proteins during the first postnatal months. CONCLUSIONS: The study contributes to the understanding of the relationship between longitudinal serum protein levels and immaturity and abnormal retinal neurovascular development. This is essential for understanding pathophysiological mechanisms and to optimize diagnosis, treatment and prevention for ROP. IMPACT: Longitudinal protein profiles of 14 extremely preterm infants were analyzed using a novel multiplex protein analysis platform combined with perinatal data. Proteins associated with gestational age at birth and the neurovascular disease ROP were identified. Among infants with ROP, longitudinal levels of the identified proteins remained largely unchanged during the first postnatal months. The main functions of the proteins identified were angiogenesis, hematopoiesis, immune function, bone regulation, lipid metabolism, and central nervous system development. The study contributes to the understanding of longitudinal serum protein patterns related to gestational age and their association with abnormal retinal neuro-vascular development.

The acute effect of metabolic cofactor supplementation: a potential therapeutic strategy against non-alcoholic fatty liver disease.

The prevalence of non-alcoholic fatty liver disease (NAFLD) continues to increase dramatically, and there is no approved medication for its treatment. Recently, we predicted the underlying molecular mechanisms involved in the progression of NAFLD using network analysis and identified metabolic cofactors that might be beneficial as supplements to decrease human liver fat. Here, we first assessed the tolerability of the combined metabolic cofactors including l-serine, N-acetyl-l-cysteine (NAC), nicotinamide riboside (NR), and l-carnitine by performing a 7-day rat toxicology study. Second, we performed a human calibration study by supplementing combined metabolic cofactors and a control study to study the kinetics of these metabolites in the plasma of healthy subjects with and without supplementation. We measured clinical parameters and observed no immediate side effects. Next, we generated plasma metabolomics and inflammatory protein markers data to reveal the acute changes associated with the supplementation of the metabolic cofactors. We also integrated metabolomics data using personalized genome-scale metabolic modeling and observed that such supplementation significantly affects the global human lipid, amino acid, and antioxidant metabolism. Finally, we predicted blood concentrations of these compounds during daily long-term supplementation by generating an ordinary differential equation model and liver concentrations of serine by generating a pharmacokinetic model and finally adjusted the doses of individual metabolic cofactors for future human clinical trials.

Dramatic changes in blood protein levels during the first week of life in extremely preterm infants.

BACKGROUND: Preterm birth and its complications are the primary cause of death among children under the age of 5. Among the survivors, morbidity both perinatally and later in life is common. The dawn of novel technical platforms for comprehensive and sensitive analysis of protein profiles in blood has opened up new possibilities to study both health and disease with significant clinical accuracy, here used to study the preterm infant and the physiological changes of the transition from intrauterine to extrauterine life. METHODS: We have performed in-depth analysis of the protein profiles of 14 extremely preterm infants using longitudinal sampling. Medical variables were integrated with extensive profiling of 448 unique protein targets. RESULTS: The preterm infants have a distinct unified protein profile in blood directly at birth regardless of clinical background; however, the pattern changed profoundly postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age. Clusters of proteins depending on temporal trend were identified. CONCLUSION: The protein profiles and the temporal trends here described will contribute to the understanding of the physiological changes in the intrauterine-extrauterine transition, which is essential to adjust early-in-life interventions to prone a normal development in the vulnerable preterm infants. IMPACT: We have performed longitudinal and in-depth analysis of the protein profiles of 14 extremely preterm infants using a novel multiplex protein analysis platform. The preterm infants had a distinct unified protein profile in blood directly at birth regardless of clinical background. The pattern changed dramatically postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age. Certain clusters of proteins were identified depending on their temporal trend, including several liver and immune proteins. The study contributes to the understanding of the physiological changes in the intrauterine-extrauterine transition.

Heterogenous Clinical Landscape in a Consanguineous Malonic Aciduria Family.

Malonic aciduria is an extremely rare inborn error of metabolism due to malonyl-CoA decarboxylase deficiency. This enzyme is encoded by the MLYCD (Malonyl-CoA Decarboxylase) gene, and the disease has an autosomal recessive inheritance. Malonic aciduria is characterized by systemic clinical involvement, including neurologic and digestive symptoms, metabolic acidosis, hypoglycemia, failure to thrive, seizures, developmental delay, and cardiomyopathy. We describe here two index cases belonging to the same family that, despite an identical genotype, present very different clinical pictures. The first case is a boy with neonatal metabolic symptoms, abnormal brain MRI, and dilated cardiomyopathy. The second case, the cousin of the first patient in a consanguineous family, showed later symptoms, mainly with developmental delay. Both patients showed high levels of malonylcarnitine on acylcarnitine profiles and malonic acid on urinary organic acid chromatographies. The same homozygous pathogenic variant was identified, c.346C > T; p. (Gln116*). We also provide a comprehensive literature review of reported cases. A review of the literature yielded 52 cases described since 1984. The most common signs were developmental delay and cardiomyopathy. Increased levels of malonic acid and malonylcarnitine were constant. Presentations ranged from neonatal death to patients surviving past adolescence. These two cases and reported patients in the literature highlight the inter- and intrafamilial variability of malonic aciduria.

Optimization of ion trajectories in a dynamically harmonized Fourier-transform ion cyclotron resonance cell using a design of experiments strategy.

RATIONALE: With the recent introduction of the dynamically harmonized Fourier-transform ion cyclotron resonance (FT-ICR) cell, the complexity of tuning has expanded drastically, and fine-tuning of the direct current voltages is required to optimize the ion cloud movement. As this adjustment must typically be performed manually, more reliable computational methods would be useful. METHODS: Here we propose a computational method based on a design of experiments (DoE) strategy to overcome the limits of classical manual tuning. This DoE strategy was exemplarily applied on a 12 T FT-ICR instrument equipped with a dynamically harmonized ICR cell. The chemometric approach, based on a central composite face (CCF) design, was first applied to a reference material (sodium trifluoroacetate) allowing for the evaluation of the primary cell parameters. Eight factors related to shimming and gating were identified. The summed intensity of the signal corresponding to the even harmonics was defined as one quality criterion. RESULTS: The DoE response allowed for rapid and complete mapping of cell parameters resulting in an optimized parameter set. The new set of cell parameters was applied to the study of an ultra-complex sample: Tholins, an ultra-complex mixture that mimics the haze present on Titan, was chosen. We observed a substantial improvement in mass spectrometric performance. The sum of signals related to harmonics was decreased by a factor of three (from 4% for conventional tuning to 1.3%). Furthermore, the dynamic range was also increased, which in turn led to an increase in attributed peaks by 13%. CONCLUSIONS: This computational procedure based on an experimental design can be applied to any other mass spectrometric parameter optimization problem. This strategy will lead to a more transparent and data-driven method development.

A new optimization strategy for MALDI FTICR MS tissue analysis for untargeted metabolomics using experimental design and data modeling.

Ultra-high-resolution imaging mass spectrometry using matrix-assisted laser desorption ionization (MALDI) MS coupled to a Fourier transform ion cyclotron resonance (FTICR) mass analyzer is a powerful technique for the visualization of small molecule distribution within biological tissues. The FTICR MS provides ultra-high resolving power and mass accuracy that allows large molecular coverage and molecular formula assignments, both essential for untargeted metabolomics analysis. These performances require fine optimizations of the MALDI FTICR parameters. In this context, this study proposes a new strategy, using experimental design, for the optimization of ion transmission voltages and MALDI parameters, for tissue untargeted metabolomics analysis, in both positive and negative ionization modes. These experiments were conducted by assessing the effects of nine factors for ion transmission voltages and four factors for MALDI on the number of peaks, the weighted resolution, and the mean error within m/z 150-1000 mass range. For this purpose, fractional factorial designs were used with multiple linear regression (MLR) to evaluate factor effects and to optimize parameter values. The optimized values of ion transmission voltages (RF amplitude TOF, RF amplitude octopole, frequency transfer optic, RF frequency octopole, deflector plate, funnel 1, skimmer, funnel RF amplitude, time-of-flight, capillary exit), MALDI parameters (laser fluence, number of laser shots), and detection parameters (data size, number of scans) led to an increase of 32% and 18% of the number of peaks, an increase of 8% and 39% of the resolution, and a decrease of 56% and 34% of the mean error in positive and negative ionization modes, respectively. Graphical abstract.

Analysis of Mucopolysaccharidosis Type VI through Integrative Functional Metabolomics.

Metabolic phenotyping is poised as a powerful and promising tool for biomarker discovery in inherited metabolic diseases. However, few studies applied this approach to mcopolysaccharidoses (MPS). Thus, this innovative functional approach may unveil comprehensive impairments in MPS biology. This study explores mcopolysaccharidosis VI (MPS VI) or Maroteaux⁻Lamy syndrome (OMIM #253200) which is an autosomal recessive lysosomal storage disease caused by the deficiency of arylsulfatase B enzyme. Urine samples were collected from 16 MPS VI patients and 66 healthy control individuals. Untargeted metabolomics analysis was applied using ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry. Furthermore, dermatan sulfate, amino acids, carnitine, and acylcarnitine profiles were quantified using liquid chromatography coupled to tandem mass spectrometry. Univariate analysis and multivariate data modeling were used for integrative analysis and discriminant metabolites selection. Pathway analysis was done to unveil impaired metabolism. The study revealed significant differential biochemical patterns using multivariate data modeling. Pathway analysis revealed that several major amino acid pathways were dysregulated in MPS VI. Integrative analysis of targeted and untargeted metabolomics data with in silico results yielded arginine-proline, histidine, and glutathione metabolism being the most affected. This study is one of the first metabolic phenotyping studies of MPS VI. The findings might shed light on molecular understanding of MPS pathophysiology to develop further MPS studies to enhance diagnosis and treatments of this rare condition.

Unveiling metabolic remodeling in mucopolysaccharidosis type III through integrative metabolomics and pathway analysis.

BACKGROUND: Metabolomics represent a valuable tool to recover biological information using body fluids and may help to characterize pathophysiological mechanisms of the studied disease. This approach has not been widely used to explore inherited metabolic diseases. This study investigates mucopolysaccharidosis type III (MPS III). A thorough and holistic understanding of metabolic remodeling in MPS III may allow the development, improvement and personalization of patient care. METHODS: We applied both targeted and untargeted metabolomics to urine samples obtained from a French cohort of 49 patients, consisting of 13 MPS IIIA, 16 MPS IIIB, 13 MPS IIIC, and 7 MPS IIID, along with 66 controls. The analytical strategy is based on ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry. Twenty-four amino acids have been assessed using tandem mass spectrometry combined with liquid chromatography. Multivariate data modeling has been used for discriminant metabolite selection. Pathway analysis has been performed to retrieve metabolic pathways impairments. RESULTS: Data analysis revealed distinct biochemical profiles. These metabolic patterns, particularly those related to the amino acid metabolisms, allowed the different studied groups to be distinguished. Pathway analysis unveiled major amino acid pathways impairments in MPS III mainly arginine-proline metabolism and urea cycle metabolism. CONCLUSION: This represents one of the first metabolomics-based investigations of MPS III. These results may shed light on MPS III pathophysiology and could help to set more targeted studies to infer the biomarkers of the affected pathways, which is crucial for rare conditions such as MPS III.

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome.

Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery.

This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.

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.

Methylmalonyl-CoA Epimerase Deficiency Mimicking Propionic Aciduria.

Methylmalonyl-CoA epimerase (MCE) converts d-methylmalonyl-CoA epimer to l-methylmalonyl-CoA epimer in the propionyl-CoA to succinyl-CoA pathway. Only seven cases of MCE deficiency have been described. In two cases, MCE deficiency was combined with sepiapterin reductase deficiency. The reported clinical pictures of isolated MCE are variable, with two asymptomatic patients and two other patients presenting with metabolic acidosis attacks. For combined MCE and sepiapterin reductase deficiency, the clinical picture is dominated by neurologic alterations. We report isolated MCE deficiency in a boy who presented at five years of age with acute metabolic acidosis. Metabolic investigations were consistent with propionic aciduria (PA). Unexpectedly, propionyl-CoA carboxylase activity was within the reference range. Afterward, apparently intermittent and mild excretion of methylmalonic acid (MMA) was discovered. Methylmalonic pathway gene set analysis using the next-generation sequencing approach allowed identification of the common homozygous nonsense pathogenic variant (c.139C > T-p.Arg47*) in the methylmalonyl-CoA epimerase gene (MCEE). Additional cases of MCE deficiency may help provide better insight regarding the clinical impact of this rare condition. MCE deficiency could be considered a cause of mild and intermittent increases in methylmalonic acid.

Pyridoxine-dependent epilepsy: report on three families with neuropathology.

Pyridoxine-dependent epilepsy (PDE) is a pharmacoresistant epileptogenic encephalopathy controlled by pyridoxine supplementation at pharmacological doses. Despite supplementation, the long-term outcome is often poor possibly because of recurrent seizures and developmental structural brain abnormalities. We report on five patients with PDE from three unrelated families. The diagnosis was confirmed by ALDH7A1 sequencing, which allowed for the characterization of two homozygous variations [NM_001182.3:c.1279G > C - p.(Glu427Gln) and c.834G > A - p.(Val278Val)]. Brain autopsy was conducted for one untreated patient with molecularly confirmed antiquitin deficiency. Macroscopic and histological examination revealed a combination of lesions resulting from recurrent seizures and consisting of extensive areas of cortical necrosis, gliosis, and hippocampic sclerosis. The examination also revealed developmental abnormalities including corpus callosum dysgenesis and corticospinal pathfinding anomalies. This case is the second to be reported in the literature, and our findings show evidence that antiquitin is required for normal brain development and functioning. Despite prophylactic prenatal pyridoxine supplementation during the last trimester of pregnancy in one of the three families and sustained pyridoxine treatment in three living patients, the clinical outcome remained poor with delayed acquisition of neurocognitive skills. Combined therapy (pyridoxine/arginine supplementation and lysine-restricted diet) should be considered early in the course of the disease for a better long-term outcome. Enhanced knowledge of PDE features is required to improve treatment strategies.

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

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

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

Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of "omic" technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent "omic" technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era.