Short‐Term Stability of Whole Blood Polyunsaturated Fatty Acid Content on Filter Paper During Storage at −28 °C

Pupillo, Daniele; Simonato, Manuela; Cogo, Paola; Lapillonne, Alexandre; Carnielli, Virgilio P.

doi:10.1007/s11745-015-4111-z

Cited by 13 publications

(16 citation statements)

References 27 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%

“…Measurements of small molecules in archived DBS can be affected by extraction methods, chromatography, MS ionization (Bruce et al 2009; Contrepois et al 2015; Michopoulos et al 2010; Raju et al 2016) as well as DBS aging and storage (Liu et al 2014; Pupillo et al 2016; Vu et al 2011). In addition, a major concern in untargeted analysis of DBS is the effect of blood haematocrit, which can have a strong impact on quantitation when less than a whole spot is available for analysis.…”

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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“…Ideal storage conditions for DBS small molecule studies were found to be in low gas‐permeable zip‐closure bags with desiccant, humidity indicator cards, and lower temperatures (4°C or –80°C) for enhanced stability . Further, lipidomics studies focusing on PUFA or oxylipins often use DBS filter paper pretreated with butylated hydroxytoluene and a chelating agent which is then stored at –80°C (ideal) indefinitely to prevent degradation or room temperature for up to 6 months . However, sometimes samples collected 10–20 years ago are not stored under optimal conditions or these conditions are not available in remote areas, affecting the data quality from longitudinal studies.…”

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confidence: 99%

Comparing identified and statistically significant lipids and polar metabolites in 15‐year old serum and dried blood spot samples for longitudinal studies

Kyle

Casey

Stratton

et al. 2017

Rapid Comm Mass Spectrometry

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The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as the smaller blood volume required, storage at room temperature, and ability for sampling in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. Here we analyzed the stability of polar metabolites and lipids in DBS samples collected in 2000-2001 and stored at room temperature. The identified and statistically significant molecules were then compared to matched serum samples stored at −80°C to determine if the DBS samples could be effectively used in a longitudinal study following metabolic disease. Four hundred polar metabolites and lipids were identified in the serum and DBS samples using gas chromatograph-mass spectrometry (GC-MS), liquid chromatography-MS (LC-MS) and LC-ion mobility spectrometry-MS (LC-IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant metabolite was conserved in a case-control study of older diabetic males with high body mass indices, triacylglycerides and glucose levels, and low amounts of high density lipoproteins and non-diabetic patients with normal levels, indicating that degradation in the DBS samples affects quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, thirty-six statistically significant lipids correlated in both sample types indicating that the lipids did not degrade as much as the polar metabolites in the DBS samples and quantitation was still possible.

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“…Each untargeted metabolomics dataset has a unique and often complex set of normalization requirements, such as adjustment for sample batch, run-order, processing and storage, dilution factors (e.g., creatinine for urine or potassium for dried blood spots), and known experimental contaminants (Pupillo et al, 2016). Therefore, to objectively select a suitable scheme for normalizing a given metabolomics dataset, we use the Bioconductor R package scone (Cole and Risso, 2017).…”

Section: Data-adaptive Normalization With Sconementioning

confidence: 99%

“…Because the biological factor of interest is breastfeeding, two fatty acids that are abundant in breast milk, i.e., palmitoleic acid and docosahexaenoic acid (DHA) (Chuang et al, 2013;Gardner et al, 2017), were used as positive controls, selected prior to any analysis. Known sources of technical variation in these samples include NBS age, potassium level (a measure of hematocrit), run-order, and batch (De Kesel et al, 2014;Pupillo et al, 2016).…”

Section: Metabolomics Of Neonatal Blood Spotsmentioning

confidence: 99%

Data-adaptive pipeline for filtering and normalizing metabolomics data

Schiffman

Petrick

Perttula

et al. 2018

Preprint

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IntroductionUntargeted metabolomics datasets contain large proportions of uninformative features and are affected by a variety of nuisance technical effects that can bias subsequent statistical analyses. Thus, there is a need for versatile and data-adaptive methods for filtering and normalizing data prior to investigating the underlying biological phenomena. ConclusionOur proposed data-adaptive pipeline is intuitive and effectively reduces technical noise from untargeted metabolomics datasets. It is particularly relevant for interrogation of biological phenomena in data derived from complex matrices associated with biospecimens.

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Short‐Term Stability of Whole Blood Polyunsaturated Fatty Acid Content on Filter Paper During Storage at −28 °C

Cited by 13 publications

References 27 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

Comparing identified and statistically significant lipids and polar metabolites in 15‐year old serum and dried blood spot samples for longitudinal studies

Data-adaptive pipeline for filtering and normalizing metabolomics data

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