The development and validation of a fast and robust dried blood spot based lipid profiling method to study infant metabolism

Koulman, Albert; Prentice, Philippa; Wong, Ma Li; Matthews, Lee; Bond, Nicholas J.; Eiden, Michael; Griffin, Julian L.; Dunger, David B.

doi:10.1007/s11306-014-0628-z

Cited by 89 publications

(121 citation statements)

References 24 publications

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“…Since ethnicity and sex are dichotomous variables, birth weight and DBS-age variables were standardized by subtracting the mean and dividing by the standard deviation. The DBS-age covariate was included to adjust for any changes in feature intensity due to storage conditions (Koulman et al 2014; Pupillo et al 2016). Estimated p- values obtained from the regression model were used to evaluate whether each coefficient was significantly associated with the feature abundance.…”

Section: Methodsmentioning

confidence: 99%

“…For example, Hazen and co-workers employed this approach to implicate joint microbial/human metabolism of the nutrient, choline, as a cause of heart disease (Koeth et al 2013; Tang et al 2013; Wang et al 2011). Previous untargeted metabolomic analyses of newborn DBS have been conducted rarely, with a few examples being the studies of Denes et al (2012), who screened for inborn errors of metabolism, and of Koulman et al (2014) and Prentice et al (2015) who investigated biomarkers of breastfeeding.…”

Section: Introductionmentioning

confidence: 99%

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An untargeted metabolomics method for archived newborn dried blood spots in epidemiologic studies

et al. 2017

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Introduction For pediatric diseases like childhood leukemia, a short latency period points to in-utero exposures as potentially important risk factors. Untargeted metabolomics of small molecules in archived newborn dried blood spots (DBS) offers an avenue for discovering early-life exposures that contribute to disease risks. Objectives The purpose of this study was to develop a quantitative method for untargeted analysis of archived newborn DBS for use in an epidemiological study (California Childhood Leukemia Study, CCLS). Methods Using experimental DBS from the blood of an adult volunteer, we optimized extraction of small molecules and integrated measurement of potassium as a proxy for blood hematocrit. We then applied this extraction method to 4.7-mm punches from 106 control DBS samples from the CCLS. Sample extracts were analyzed with liquid chromatography high resolution mass spectrometry (LC-HRMS) and an untargeted workflow was used to screen for metabolites that discriminate population characteristics such as sex, ethnicity, and birth weight. Results Thousands of small molecules were measured in extracts of archived DBS. Normalizing for potassium levels removed variability related to varying hematocrit across DBS punches. Of the roughly 1,000 prevalent small molecules that were tested, multivariate linear regression detected significant associations with ethnicity (3 metabolites) and birth weight (15 metabolites) after adjusting for multiple testing. Conclusions This untargeted workflow can be used for analysis of small molecules in archived DBS to discover novel biomarkers, to provide insights into the initiation and progression of diseases, and to provide guidance for disease prevention.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An untargeted metabolomics method for archived newborn dried blood spots in epidemiologic studies

et al. 2017

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“…DBS is a standard sample matrix in newborn screening to profile for inherited diseases, because only a small volume of blood per spot from heel prick is needed (<50 μL) [66]. Targeted metabolomics is the method most often used to analyze DBS [67, 68].…”

Section: The Selection Of Blood-collection Tubesmentioning

confidence: 99%

Effects of pre-analytical processes on blood samples used in metabolomics studies

2015

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Every day, analytical and bio-analytical chemists make sustained efforts to improve the sensitivity, specificity, robustness, and reproducibility of their methods. Especially in targeted and non-targeted profiling approaches, including metabolomics analysis, these objectives are not easy to achieve; however, robust and reproducible measurements and low coefficients of variation (CV) are crucial for successful metabolomics approaches. Nevertheless, all efforts from the analysts are in vain if the sample quality is poor, i.e. if preanalytical errors are made by the partner during sample collection. Preanalytical risks and errors are more common than expected, even when standard operating procedures (SOP) are used. This risk is particularly high in clinical studies, and poor sample quality may heavily bias the CV of the final analytical results, leading to disappointing outcomes of the study and consequently, although unjustified, to critical questions about the analytical performance of the approach from the partner who provided the samples. This review focuses on the preanalytical phase of liquid chromatography–mass spectrometry-driven metabolomics analysis of body fluids. Several important preanalytical factors that may seriously affect the profile of the investigated metabolome in body fluids, including factors before sample collection, blood drawing, subsequent handling of the whole blood (transportation), processing of plasma and serum, and inadequate conditions for sample storage, will be discussed. In addition, a detailed description of latent effects on the stability of the blood metabolome and a suggestion for a practical procedure to circumvent risks in the preanalytical phase will be given.Graphical AbstractThe procedures and potential problems in preanalytical aspects of metabolomics studies using blood samples. Bias in the preanalytical phase may lead to unwanted results in the subsequential studies

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“…Applications of microsampling in metabolomics have been presented using DBS sampling [11][12][13][14][15][16][17]. Nevertheless, these studies are still at an early stage and important pre-analytical strategies need to be carefully evaluated.…”

Section: Introductionmentioning

confidence: 99%

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow

et al. 2017

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Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at − 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. KeywordsMetabolomics; Volumetric absorptive microsampling; Mass spectrometry ✉ Giuseppe Paglia beppepaglia@gmail.com. Compliance with ethical standardsThis study was performed in accordance with the ethical standards. The local ethics committee (Comitato etico del comprensorio sanitario di Bolzano) approved the study, and all participants provided written informed consent.

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The development and validation of a fast and robust dried blood spot based lipid profiling method to study infant metabolism

Cited by 89 publications

References 24 publications

An untargeted metabolomics method for archived newborn dried blood spots in epidemiologic studies

An untargeted metabolomics method for archived newborn dried blood spots in epidemiologic studies

Effects of pre-analytical processes on blood samples used in metabolomics studies

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow

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