Signature Mapping (SigMa): An efficient approach for processing complex human urine 1H NMR metabolomics data

Khakimov, Bekzod; Mobaraki, Nabiollah; Trimigno, Alessia; Aru, Violetta; Engelsen, Søren B.

doi:10.1016/j.aca.2020.02.025

Cited by 55 publications

(61 citation statements)

References 35 publications

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“…Scaling the NMR spectra according to the area of the ERETIC signal minimizes variations originating from the NMR experiment and allows for inter-laboratory data comparisons. Unlike urine NMR spectra 24 , shifting of the entire 1 H NMR spectra of blood plasma samples towards the doublet of alanine is sufficient to eliminate minor misalignments present in the spectra due to small differences in pH and/or experimental error (e.g. plasma to buffer ratio, small fluctuations on spectrum acquisition temperature).…”

Section: Resultsmentioning

confidence: 99%

“…However, the SR of subfractions belonging to the same main fraction and the same molecular type were similar, though they possessed clear trends of chemical shift changes in cholesterol methyl, LP methyl and methylene signals according to the particle size. complex 1 H NMR metabolomics datasets 24,35 . The software is based on the latest developments in the NMR spectral data processing methods and through the regression models developed in this study, and able to predict LP concentrations from human blood plasma using 1 H NMR NOESY spectra.…”

Section: Spectral Signatures Of Lp Depend On Particle Sizementioning

confidence: 99%

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Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance

Khakimov¹,

Hoefsloot

Mobaraki

et al. 2021

Preprint

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Lipoprotein subfractions are biomarkers for early diagnosis of cardiovascular diseases. The reference method, ultracentrifugation, for measuring lipoproteins is time consuming and there is a need to develop a rapid method for cohort screenings. Here we present partial least squares regression models developed using 1H-NMR spectra and concentrations of lipoproteins as measured by ultracentrifugation on 316 healthy Danes. Different regions of the 1H-NMR spectra representing signals of the lipoproteins and different lipid species were investigated to develop parsimonious, reliable and best performing prediction models. 65 LP main and subfractions were predictable with an accuracy Q2 of > 0.6 on test set samples. The models were tested on an independent cohort of 290 healthy Swedes with predicted and reference values matching by up to 85-95%. The software was developed to predict lipoproteins in human blood using 1H-NMR spectra and made freely available to be applied for future cohort screenings.

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Section: Resultsmentioning

confidence: 99%

Section: Spectral Signatures Of Lp Depend On Particle Sizementioning

confidence: 99%

Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance

Khakimov¹,

Hoefsloot

Mobaraki

et al. 2021

Preprint

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“…The application of interval selection proved to be a powerful tool to focus on the relevant information and discard noisy data. SigMa software [ 36 ] was used in this study to identify and quantify the molecules present in the samples and will possibly in the future contain a specific library for foods such as milk. This can help in future studies to have a more robust picture of the kinetics of determined molecules of interest.…”

Section: Discussionmentioning

confidence: 99%

“…Spectra, after normalization to receiver gain, were then processed using SigMa software [ 36 ]. They were initially referenced to the TSP signal at 0.0 ppm, then pre-aligned using large spectral regions and employing the icoshift algorithm [ 37 ].…”

Section: Methodsmentioning

confidence: 99%

An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality

et al. 2020

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A great number of factors can influence milk fermentation for yoghurt production such as fermentation conditions, starter cultures and milk characteristics. It is important for dairy companies to know the best combinations of these parameters for a controlled fermentation and for the desired qualities of yoghurt. This study investigates the use of a 1H-NMR metabolomics approach to monitor the changes in milk during fermentation from time 0 to 24 h, taking samples every hour in the first 8 h and then at the end-point at 24 h. Three different starter cultures (L. delbrueckii ssp. bulgaricus, S. thermophilus and their combination) were used and two different heat treatments (99 or 105 °C) were applied to milk. The results clearly show the breakdown of proteins and lactose as well as the concomitant increase in acetate, lactate and citrate during fermentation. Formate is found at different initial concentrations depending on the heat treatment of the milk and its different time trajectory depends on the starter cultures: Lactobacillus cannot produce formate, but needs it for growth, whilst Streptococcus is able to produce formate from pyruvate, therefore promoting the symbiotic relationship between the two strains. On the other hand, Lactobacillus can hydrolyze milk proteins into amino acids, enriching the quality of the final product. In this way, better insight into the protocooperation of lactic acid bacteria strains and information on the impact of a greater heat treatment in the initial matrix were obtained. The global chemical view on the fermentations provided using NMR is key information for yoghurt producers and companies producing starter cultures.

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“…FIDs were Fourier transformed after multiplied with an exponential function corresponding to a line broadening of 0.3 Hz, followed by automated phasing and baseline correction. Raw 1H NMR was then converted into a metabolite table using SigMa [28].…”

Section: H Nmr Spectroscopy Of Blood Plasmamentioning

confidence: 99%

A Multi-Omics Approach Reveals New Signatures in Obese Allergic Asthmatic Children

et al. 2020

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Background: Asthma is a multifactorial condition where patients with identical clinical diagnoses do not have the same clinical history or respond to treatment. This clinical heterogeneity is reflected in the definition of two main endotypes. We aimed to explore the metabolic and microbiota signatures that characterize the clinical allergic asthma phenotype in obese children. Methods: We used a multi-omics approach combining clinical data, plasma and fecal inflammatory biomarkers, metagenomics, and metabolomics data in a cohort of allergic asthmatic children. Results: We observed that the obese allergic asthmatic phenotype was markedly associated with higher levels of leptin and lower relative proportions of plasma acetate and a member from the Clostridiales order. Moreover, allergic children with a worse asthma outcome showed higher levels of large unstained cells, fecal D lactate and D/L lactate ratio, and with a higher relative proportion of plasma creatinine and an unclassified family member from the RF39 order belonging to the Mollicutes class. Otherwise, children with persistent asthma presented lower levels of plasma citrate and dimethylsulfone. Conclusion: Our integrative approach shows the molecular heterogeneity of the allergic asthma phenotype while highlighting the use of omics technologies to examine the clinical phenotype at a more holistic level.

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Signature Mapping (SigMa): An efficient approach for processing complex human urine 1H NMR metabolomics data

Cited by 55 publications

References 35 publications

Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance

Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance

An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality

A Multi-Omics Approach Reveals New Signatures in Obese Allergic Asthmatic Children

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Signature Mapping (SigMa): An efficient approach for processing complex human urine 1H NMR metabolomics data

Cited by 55 publications

References 35 publications

Human blood lipoprotein predictions from 1H NMR spectra: protocol, model performances and cage of covariance

Human blood lipoprotein predictions from 1H NMR spectra: protocol, model performances and cage of covariance

An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality

A Multi-Omics Approach Reveals New Signatures in Obese Allergic Asthmatic Children

Contact Info

Product

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Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance

Human blood lipoprotein predictions from ¹H NMR spectra: protocol, model performances and cage of covariance