Metabolomic Profiling of Human Urine as a Screen for Multiple Inborn Errors of Metabolism

Kennedy, Adam D.; Miller, Marcus J.; Beebe, Kirk; Wulff, Jacob; Evans, Anne M.; Miller, Luke A. D.; Sutton, V. Reid; Sun, Qin; Elsea, Sarah H.

doi:10.1089/gtmb.2015.0291

Cited by 49 publications

(58 citation statements)

References 24 publications

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“…The analysis of EDTA plasma identified 777 biochemicals, and the analysis of urine revealed 670 biochemicals (Figure 3) and similar to other cohorts analyzed with the same technology [23,24]. …”

Section: Resultssupporting

confidence: 72%

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Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

Kennedy

Pappan

Donti

et al. 2017

Molecular Genetics and Metabolism

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We sought to determine the molecular composition of human cerebrospinal fluid (CSF) and identify the biochemical pathways represented in CSF to understand the potential for untargeted screening of inborn errors of metabolism (IEMs). Biochemical profiles for each sample were obtained using an integrated metabolomics workflow comprised of four chromatographic techniques followed by mass spectrometry. Secondarily, we wanted to compare the biochemical profile of CSF with those of plasma and urine within the integrated mass spectrometric-based metabolomic workflow. Three sample types, CSF (N=30), urine (N=40) and EDTA plasma (N=31), were analyzed from retrospectively collected pediatric cohorts of equivalent age and gender characteristics. We identified 435 biochemicals in CSF epresenting numerous biological and chemical/structural families. Sixty-three percent (273 of 435) of the biochemicals detected in CSF also were detected in urine and plasma, another 32% (140 of 435) were detected in either plasma or urine, and 5% (22 of 435) were detected only in CSF.Analyses of several metabolites showed agreement between clinically useful assays and the metabolomics approach. An additional set of CSF and plasma samples collected from the same patient revealed correlation between several biochemicals detected in paired samples. Finally, analysis of CSF from a pediatric case with dihydropteridine reductase (DHPR) deficiency demonstrated the utility of untargeted global metabolic phenotyping as a broad assessment to screen samples from patients with undifferentiated phenotypes. The results indicate a single CSF sample processed with an integrated metabolomics workflow can be used to identify a large breadth of biochemicals that could be useful for identifying disrupted metabolic patterns associated with IEMs.

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Section: Resultssupporting

confidence: 72%

“…We recently demonstrated the utility of metabolomics to identify biochemical signatures of disease in plasma [23] and urine [24] for diverse classes of IEMs. This approach identified and assisted in the diagnosis of aromatic amino acid decarboxylase deficiency through the metabolomic and genomic analyses of plasma [22].…”

Section: Introductionmentioning

confidence: 99%

Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

Kennedy

Pappan

Donti

et al. 2017

Molecular Genetics and Metabolism

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“…Once a methodology is developed for comparison of the global metabolomic data between the reference population and the clinical sample, a statistical method must be employed to determine if the levels of any biochemicals in the clinical sample are perturbed with respect to the reference cohort. Z‐scoring, in relation to expected levels defined by the reference cohort, is an appropriate statistical method to identify deviations in the biochemical levels in the clinical sample possibly reflective of health status and has been used in cases where a highly penetrant genetic mutation was known or suspected …”

Section: Methodology Considerationsmentioning

confidence: 99%

“…Small biochemicals can be defined as compounds ≤1000 m/z and include all metabolites in a biological sample—whether plasma, cerebrospinal fluid, urine, cells, or other tissue. Classes of small molecules detected by metabolomics include amino acids, carbohydrates, energy metabolites, lipids, vitamins, co‐factors, nucleotides, and xenobiotics obtained from the diet, environmental exposure, microbiota metabolism, and pharmacotherapy . Like other classes of molecules, peptides can be distinguished on metabolomics platforms.…”

Section: Introductionmentioning

confidence: 99%

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

et al. 2018

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Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome—all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n‐of‐1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.

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“…This finding amplifies the need to examine multiple downstream molecular levels including the transcriptome, proteome, lipidome and metabolome to identify critical driver events and discover molecular manifestation governing biochemical processes. Another example is inborn errors of metabolism (IEM), where metabolite measurements allow for a high confidence diagnosis of a genetic defect [14]. However, in some of the IEM patients studied, genotype-phenotype correlation was not well pronounced, possibly due to influence from other therapeutic interventions.…”

Section: What Makes Metabolomics Necessary?mentioning

confidence: 99%

Clinical metabolomics: a pivotal tool for companion diagnostic development and precision medicine

Tolstikov¹,

Akmaev²,

Sarangarajan³

et al. 2017

Expert Review of Molecular Diagnostics

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Metabolomic Profiling of Human Urine as a Screen for Multiple Inborn Errors of Metabolism

Cited by 49 publications

References 24 publications

Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

Clinical metabolomics: a pivotal tool for companion diagnostic development and precision medicine

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