A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism

Jacob, Mohan V.; Malkawi, Abeer; Albast, Nour; Bougha, Salam Al; Lopata, Andreas L.; Dasouki, Majed; Rahman, Anas M. Abdel

doi:10.1016/j.aca.2018.03.058

Cited by 82 publications

(64 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…targeted metabolomics of neonatal dry blood spot. Targeted metabolomic profiling of dry blood spots (DBSs) was carried out according to a previously reported protocol 18 with some adjustments. Briefly, each DBS sample was punched into a 96-well plate, and metabolites were extracted using internal standard containing extraction solvent (50% MeOH, 50% ACN, 250 nM internal standard).…”

Section: Demographic Data and Sample Collectionmentioning

confidence: 99%

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Zhao¹,

Ge²,

Li³

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Gestational Diabetes Mellitus (GDM), which is correlated with changes in the gut microbiota, is a risk factor for neonatal inborn errors of metabolism (ieMs). Maternal hyperglycemia exerts epigenetic effects on genes that encode IEM-associated enzymes, resulting in changes in the neonatal blood metabolome. However, the relationship between maternal gut microbiota and the neonatal blood metabolome remains poorly understood. this study aimed at understanding the connections between maternal gut microbiota and the neonatal blood metabolome in GDM. 1H-NMR-based untargeted metabolomics was performed on maternal fecal samples and targeted metabolomics on the matched neonatal dry blood spots from a cohort of 40 pregnant women, including 22 with GDM and 18 controls. Multi-omic association methods (including Co-Inertia Analysis and Procrustes Analysis) were applied to investigate the relationship between maternal fecal metabolome and the neonatal blood metabolome. Both maternal fecal metabolome and the matched neonatal blood metabolome could be separated along the vector of maternal hyperglycemia. A close relationship between the maternal and neonatal metabolomes was observed by multi-omic association approaches. Twelve out of thirty-two maternal fecal metabolites with altered abundances from 872 1H-NMR features (Bonferroni-adjusted P < 0.05) in women with GDM and the controls were identified, among which 8 metabolites contribute (P < 0.05 in a 999-step permutation test) to the close connection between maternal and the neonatal metabolomes in GDM. Four of these eight maternal fecal metabolites, including lysine, putrescine, guanidinoacetate, and hexadecanedioate, were negatively associated (Spearman rank correlation, coefficient value < −0.6, P < 0.05) with maternal hyperglycemia. Biotin metabolism was enriched (Bonferroni-adjusted P < 0.05 in the hypergeometric test) with the four-hyperglycemia associated fecal metabolites. the results of this study suggested that maternal fecal metabolites contribute to the connections between maternal fecal metabolome and the neonatal blood metabolome and may further affect the risk of IEMs. Gestational diabetes mellitus (GDM) has attracted worldwide public health concern due to its adverse maternal, fetal and neonatal outcomes. GDM is a serious pregnancy complication with various risk factors 1 , including overweight, obesity, a family history of diabetes, advanced maternal age, etc. GDM has been linked with an increased risk of inborn errors of metabolism (IEMs) in offspring 2,3. IEMs are caused by inherited genetic defects and can be influenced by environmental stimuli 4. Accumulating evidence suggests that maternal hyperglycemia is associated

show abstract

Section: Demographic Data and Sample Collectionmentioning

confidence: 99%

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Zhao¹,

Ge²,

Li³

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…This diagnostic process is laborious, time-consuming, expensive, and delays diagnosis and, consequently, specific treatment. Targeted assays including multiple metabolite groups have been developed to address these issues [2,3]. Targeted assays are optimized for the physicochemical properties of the biomarkers and the matrices of the samples, which, in general, result in reliable (semi-) quantitative analyses.…”

Section: Introductionmentioning

confidence: 99%

Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform

et al. 2019

View full text Add to dashboard Cite

Routine diagnostic screening of inborn errors of metabolism (IEM) is currently performed by different targeted analyses of known biomarkers. This approach is time-consuming, targets a limited number of biomarkers and will not identify new biomarkers. Untargeted metabolomics generates a global metabolic phenotype and has the potential to overcome these issues. We describe a novel, single platform, untargeted metabolomics method for screening IEM, combining semi-automatic sample preparation with pentafluorophenylpropyl phase (PFPP)-based UHPLC- Orbitrap-MS. We evaluated analytical performance and diagnostic capability of the method by analysing plasma samples of 260 controls and 53 patients with 33 distinct IEM. Analytical reproducibility was excellent, with peak area variation coefficients below 20% for the majority of the metabolites. We illustrate that PFPP-based chromatography enhances identification of isomeric compounds. Ranked z-score plots of metabolites annotated in IEM samples were reviewed by two laboratory specialists experienced in biochemical genetics, resulting in the correct diagnosis in 90% of cases. Thus, our untargeted metabolomics platform is robust and differentiates metabolite patterns of different IEMs from those of controls. We envision that the current approach to diagnose IEM, using numerous tests, will eventually be replaced by untargeted metabolomics methods, which also have the potential to discover novel biomarkers and assist in interpretation of genetic data.

show abstract

“…These methods were utilized to investigate the translation of the neurotransmitter metabolic pathway in ve brain regions (hippocampus, striatum, hypothalamus, temporal lobe, and frontal lobe) of SHRs treated with OA and vehicle. 24,25 This study was designed to provide complete identication of the metabolites associated with the OA treatment, resulting in a more comprehensive understanding of the intervention mechanism of OA on EH.…”

Section: Introductionmentioning

confidence: 99%

Targeted neurotransmitter metabolomics profiling of oleanolic acid in the treatment of spontaneously hypertensive rats

Rao

Yang

et al. 2019

RSC Adv.

View full text Add to dashboard Cite

show abstract

A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism

Cited by 82 publications

References 53 publications

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus

Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform

Targeted neurotransmitter metabolomics profiling of oleanolic acid in the treatment of spontaneously hypertensive rats

Contact Info

Product

Resources

About