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

Investigation into temporal changes in the human bloodstain lipidome

Bloodstains are crucial pieces of physical evidences found at violent crime scenes, providing valuable information for reconstructing forensic cases. However, there is limited data on how bloodstain lipidomes change over time after deposition. Hence, we deployed a high-throughput high-performance liquid chromatography-mass spectrometry (HPLC-MS) approach to construct lipidomic atlases of bloodstains, whole blood, plasma, and blood cells from 15 healthy adults. A time-course analysis was also performed on bloodstains deposited for up to 6 months at room temperature (~ 25°C). The molecular levels of 60 out of 400 detected lipid species differed dramatically between bloodstain and whole blood samples, with major disturbances observed in membrane glycerophospholipids. More than half of these lipids were prevalent in the cellular and plasmic fractions; approximately 27% and 10% of the identified lipids were uniquely derived from blood cells and plasma, respectively. Furthermore, a subset of 65 temporally dynamic lipid species arose across the 6-month room-temperature deposition period, with decreased triacylglycerols (TAGs) and increased lysophosphatidylcholines (LPCs) as representatives, accounting for approximately 8% of the total investigated lipids. The instability of lipids increased linearly with time, with the most variability observed in the first 10 days. This study sheds light on the impact of air-drying bloodstains on blood components at room temperature and provides a list of potential bloodstain lipid markers for determining the age of bloodstains.

Serum levels of stearic and dihomo-γ-linolenic acids can be used to diagnose cervical cancer and cervical intraepithelial neoplasia

Despite widespread cervical cancer (CC) screening programs, low participation has led to high morbidity and mortality rates, especially in developing countries. Because early-stage CC often has no symptoms, a non-invasive and convenient diagnostic method is needed to improve disease detection. In this study, we developed a new approach for differentiating both CC and cervical intraepithelial neoplasia (CIN)2/3, a precancerous lesion, from healthy individuals by exploring CC fatty acid metabolic reprogramming. Analysis of public datasets suggested that various fatty acid metabolizing enzymes were expressed at higher levels in CC tissues than in normal tissues. Correspondingly, 11 free fatty acids (FFAs) showed significantly different serum levels in CC patient samples compared with healthy donor samples. Nine of these 11 FFAs also displayed significant alterations in CIN2/3 patients. We then generated diagnostic models using combinations of these FFAs, with the optimal model including stearic and dihomo-γ-linolenic acids. Receiver operating characteristic curve analyses suggested that this diagnostic model could detect CC and CIN2/3 more accurately than using serum squamous cell carcinoma antigen level. In addition, the diagnostic model using FFAs was able to detect patients regardless of clinical stage or histological type. Overall, the serum FFA diagnostic model developed in this study could be a powerful new tool for the non-invasive early detection of CC and CIN2/3.

Dried Blood Spot Metabolome Features of Ischemic-Hypoxic Encephalopathy: A Neonatal Rat Model

Hypoxic-ischemic encephalopathy (HIE) is a severe neurological disorder caused by perinatal asphyxia with significant consequences. Early recognition and intervention are crucial, with therapeutic hypothermia (TH) being the primary treatment, but its efficacy depends on early initiation of treatment. Accurately assessing the HIE severity in neonatal care poses challenges, but omics approaches have made significant contribution to understanding its complex pathophysiology. Our study further explores the impact of HIE on the blood metabolome over time and investigated changes associated with hypothermia's therapeutic effects. Using a rat model of hypoxic-ischemic brain injury, we comprehensively analyzed dried blood spot samples for fat-soluble compounds using HPLC-MS. Our research shows significant changes in the blood metabolome after HIE, with a particularly rapid recovery of lipid metabolism observed. Significant changes in lipid metabolites were observed after 3 h of HIE, including increases in ceramides, carnitines, certain fatty acids, phosphocholines, and phosphoethanolamines, while sphingomyelins and N-acylethanolamines (NAEs) decreased (p < 0.05). Furthermore, NAEs were found to be significant features in the OPLS-DA model for HIE diagnosis, with an area under the curve of 0.812. TH showed a notable association with decreased concentrations of ceramides. Enrichment analysis further corroborated these observations, showing modulation in several key metabolic pathways, including arachidonic acid oxylipin metabolism, eicosanoid metabolism via lipooxygenases, and leukotriene C4 synthesis deficiency. Our study reveals dynamic changes in the blood metabolome after HIE and the therapeutic effects of hypothermia, which improves our understanding of the pathophysiology of HIE and could lead to the development of new rapid diagnostic approaches for neonatal HIE.

Nucleic acid degradation after long-term dried blood spot storage

Collecting and preserving biological samples in the field, particularly in remote areas in tropical forests, prior to laboratory analysis is challenging. Blood samples in many cases are used for nucleic acid-based species determination, genomics or pathogen research. In most cases, maintaining a cold chain is impossible and samples remain at ambient temperature for extended periods of time before controlled storage conditions become available. Dried blood spot (DBS) storage, blood stored on cellulose-based paper, has been widely applied to facilitate sample collection and preservation in the field for decades. However, it is unclear how long-term storage on this substrate affects nucleic acid concentration and integrity. We analysed nucleic acid quality from DBS stored on Whatman filter paper no. 3 and FTA cards for up to 15 years in comparison to cold-chain stored samples using four nucleic acid extraction methods. We examined the ability to identify viral sequences from samples of 12 free-ranging primates in the Amazon forest, using targeted hybridization capture, and determined if mitochondrial genomes could be retrieved. The results suggest that even after extended periods of storage, DBS will be suitable for some genomic applications but may be of limited use for viral pathogen research, particularly RNA viruses.

Comparison of maternal venous blood metabolomics collected as dried blood spots, dried blood microsamplers, and plasma for integrative environmental health research

Use of capillary blood devices for exposome research can deepen our understanding of the intricate relationship between environment and health, and open up new avenues for preventive and personalized medicine, particularly for vulnerable populations. While the potential of these whole blood devices to accurately measure chemicals and metabolites has been demonstrated, how untargeted metabolomics data from these samplers can be integrated with previous and ongoing environmental health studies that have used conventional blood collection approaches is not yet clear. Therefore, we performed a comprehensive comparison between relative-quantitative metabolite profiles measured in venous blood collected with dried whole blood microsamplers (DBM), dried whole blood spots (DBS), and plasma from 54 mothers in an ethnically diverse population. We determined that a majority of the 309 chemicals and metabolites showed similar median intensity rank, moderate correlation, and moderate agreement between participant-quantiled intraclass correlation coefficients (ICCs) for pair-wise comparisons among the three biomatrices. In particular, whole blood sample types, DBM and DBS, were in highest agreement across metabolite comparison metrics, followed by metabolites measured in DBM and plasma, and then metabolites measured in DBS and plasma. We provide descriptive characteristics and measurement summaries as a reference database. This includes unique metabolites that were particularly concordant or discordant in pairwise comparisons. Our results demonstrate that the range of metabolites from untargeted metabolomics data collected with DBM, DBS, and plasma provides biologically relevant information for use in independent exposome investigations. However, before meta-analysis with combined datasets are performed, robust statistical approaches that integrate untargeted metabolomics data collected on different blood matrices need to be developed.

Effects of storage temperature and time on metabolite profiles measured in dried blood spots, dried blood microsamplers, and plasma

The practical advantages of capillary whole blood collection over venipuncture plasma collection for human exposome research are well known. However, before epidemiologists, clinicians, and public health researchers employ these microvolume sample collections, a rigorous evaluation of pre-analytical storage conditions is needed to develop protocols that maximize sample stability and reliability over time. Therefore, we performed a controlled experiment of dried whole blood collected on 10 μL Mitra microsamplers (DBM), 5-mm punches of whole blood from a dried blood spot (DBS), and 10 μL of plasma, and evaluated the effects of storage conditions at 4 °C, -20 °C, or -80 °C for up to 6 months on the resulting metabolite profiles measured with untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS). At -80 °C storage conditions, metabolite profiles from DBS, DBM, and plasma showed similar stability. While DBS and DBM metabolite profiles remained similarly stable at -20 °C storage, plasma profiles showed decreased stability at -20 °C compared to -80 °C storage. At refrigerated temperatures (4 °C), metabolite profiles collected on DBM were more stable than plasma or DBS, particularly for lipid classes. These results inform robust capillary blood sample storage protocols for DBM and DBS at potentially warmer temperatures than -80 °C, which may facilitate blood collections for populations outside of a clinical setting.

Metabolite Biomarkers for Early Ischemic-Hypoxic Encephalopathy: An Experimental Study Using the NeoBase 2 MSMS Kit in a Rat Model

Hypoxic-ischemic encephalopathy (HIE) is one of the most common causes of childhood disability. Hypothermic therapy is currently the only approved neuroprotective approach. However, early diagnosis of HIE can be challenging, especially in the first hours after birth when the decision to use hypothermic therapy is critical. Distinguishing HIE from other neonatal conditions, such as sepsis, becomes a significant problem in diagnosis. This study explored the utility of a metabolomic-based approach employing the NeoBase 2 MSMS kit to diagnose HIE using dry blood stains in a Rice-Vannucci model of HIE in rats. We evaluated the diagnostic fidelity of this approach in a range between 3 and 6 h after the onset of HIE, including in the context of systemic inflammation and concomitant hypothermic therapy. Discriminant analysis revealed several metabolite patterns associated with HIE. A logistic regression model using glycine levels achieved high diagnostic fidelity with areas under the receiver operating characteristic curve of 0.94 at 3 h and 0.96 at 6 h after the onset of HIE. In addition, orthogonal partial least squares discriminant analysis, which included five metabolites, achieved 100% sensitivity and 80% specificity within 3 h of HIE. These results highlight the significant potential of the NeoBase 2 MSMS kit for the early diagnosis of HIE and could improve patient management and outcomes in this serious illness.

Identification of Metabolomic Signatures for Ischemic Hypoxic Encephalopathy Using a Neonatal Rat Model

A study was performed to determine early metabolomic markers of ischemic hypoxic encephalopathy (HIE) using a Rice-Vannucci model for newborn rats. Dried blood spots from 7-day-old male and female rat pups, including 10 HIE-affected animals and 16 control animals, were analyzed by liquid chromatography coupled with mass spectrometry (HPLC-MS) in positive and negative ion recording modes. Multivariate statistical analysis revealed two distinct clusters of metabolites in both HPLC-MS modes. Subsequent univariate statistical analysis identified 120 positive and 54 negative molecular ions that exhibited statistically significant change in concentration, with more than a 1.5-fold difference after HIE. In the HIE group, the concentrations of steroid hormones, saturated mono- and triglycerides, and phosphatidylcholines (PCs) were significantly decreased in positive mode. On the contrary, the concentration of unsaturated PCs was increased in the HIE group. Among negatively charged molecular ions, the greatest variations were found in the categories of phosphatidylcholines, phosphatidylinositols, and triglycerides. The major metabolic pathways associated with changed metabolites were analyzed for both modes. Metabolic pathways such as steroid biosynthesis and metabolism fatty acids were most affected. These results underscored the central role of glycerophospholipid metabolism in triggering systemic responses in HIE. Therefore, lipid biomarkers' evaluation by targeted HPLC-MS research could be a promising approach for the early diagnosis of HIE.

Metabolite Stability in Archived Neonatal Dried Blood Spots Used for Epidemiologic Research

Epidemiologic studies of low-frequency exposures or outcomes using metabolomics analyses of neonatal dried blood spots (DBS) often require assembly of samples with substantial differences in duration of storage. Independent assessment of stability of metabolites in archived DBS will enable improved design and interpretation of epidemiologic research utilizing DBS. Neonatal DBS routinely collected and stored as part of the California Genetic Disease Screening Program between 1983 and 2011 were used. The study population included 899 children without cancer before age 6 years, born in California. High-resolution metabolomics with liquid-chromatography mass spectrometry was performed, and the relative ion intensities of common metabolites and selected xenobiotic metabolites of nicotine (cotinine and hydroxycotinine) were evaluated. In total, we detected 26,235 mass spectral features across 2 separate chromatography methods (C18 hydrophobic reversed-phase chromatography and hydrophilic-interaction liquid chromatography). For most of the 39 metabolites related to nutrition and health status, we found no statistically significant annual trends across the years of storage. Nicotine metabolites were captured in the DBS with relatively stable intensities. This study supports the usefulness of DBS stored long-term for epidemiologic studies of the metabolome. -Omics-based information gained from DBS may also provide a valuable tool for assessing prenatal environmental exposures in child health research.

Chemical markers in marine food web: A simple workflow based on methyl tert-butyl ether extraction for fatty acids and stable isotopes assessment in plankton samples

Fatty acids (FAs) are used, often in combination with stable isotopes (SIs), as chemical biomarkers to assess the contribution of different prey to the diet of consumers and define food web structure and dynamics. Extraction of lipids is traditionally carried out using methanol (MeOH) combined with chloroform or dichloromethane, these latter being well-known environmental pollutant and potential carcinogenic agents. Recently, extraction protocols based on methyl tert-butyl ether (MTBE) and MeOH have been proposed as an alternative to halogenated solvents in lipidomic studies. However, no specific investigation has been performed to assess MTBE suitability in marine ecological studies including FA analysis together with SI measurements. We used an analytical workflow for qualitative and quantitative analysis of FAs and SIs in field samples of phytoplankton, zooplankton and the scyphomedusa Pelagia noctiluca, applying MTBE in comparison with chloroform- and dichloromethane-based protocols for total lipid extraction. Our analysis suggested that MTBE is a reliable substitute for lipid extraction in trophic ecology studies in marine planktonic organisms.

A comparative analyses of lipid ratios representing desaturase enzyme activity between preterm and term infants within the first ten weeks of life

BACKGROUND

Desaturase enzymes play a key role in several pathways including biosynthesis of poly- and mono- unsaturated fatty acids (PUFAs, MUFA). In preterm infants, desaturase enzyme activity (DA) may be a rate-limiting step in maintaining PUFAs levels during this critical developmental window and impact on long term metabolic health. The study tested the hypothesis that DA is altered in preterm infants compared to term infants in early life and may be a marker of risk or contribute to later alterations in metabolic health.

METHODS

Lipidomic analyses were conducted using blood samples from two established UK-based cohorts, involving very preterm (n = 105) and term (n = 259) infants. Blood samples were taken from term infants at birth, two and six weeks and from preterm infants when established on enteral feeds and at term corrected age. DA of the 2 groups of infants were estimated indirectly from product/precursor lipids ratios of phosphatidylcholine (PC) and triglycerides (TG) species and reported according to their postmenstrual and postnatal ages.

RESULTS

There were changes in lipid ratios representing desaturase enzyme activity in preterm infants in the first weeks of life with higher delta 6 desaturases (D6D) triglyceride (TG) indices but significantly lower delta 9 desaturase (D9D) and D6D(PC) indices. In comparison to term infants, preterm have lower delta 5 desaturase (D5D) but higher D6D indices at all postnatal ages. Although point levels of desaturase indices were different, trajectories of changes in these indices over time were similar in preterm and term infants.

CONCLUSIONS

This study findings suggest the patterns of desaturase indices in preterm infants differ from that of term infants but their trajectories of change in the first 10 weeks of life were similar. These differences of DA if they persist in later life could contribute to the mechanism of diseases in preterm adulthood and warrant further investigations.

Lipid profile variability in children at different ages measured in dried blood spots

Dried blood spot (DBS) is a minimally invasive sampling technique that has several advantages over conventional venipuncture/arterial blood sampling. More recently, DBS has also been applied for lipidomics analysis, but this is an area that requires further research. The few works found in the literature on lipidomics of DBS samples performed the analysis in adult samples, leaving pediatric ages unmapped. The objective of this study was to assess the variability of the lipid profile (identified by high-resolution C18 RP-LC-MS/MS) of DBS at pediatric age (0-10 days, 2-18 months, and 3-13 years) and to identify age-related variations. The results revealed that the lipidomic signature of the three age groups is significantly different, especially for a few species of neutral lipids and phosphatidylcholines. The main contributors to the differentiation of the groups correspond to 3 carnitine (Car), 2 cholesteryl ester (CE), 2 diacylglycerol (DG), 2 triacylglycerol (TG), 3 phosphatidylcholine (PC), 1 ether-linked PC, 1 phosphatidylethanolamine (PE), 1 ether-linked PE and 1 phosphatidylinositol (PI) species, all with statistically significant differences. Additionally, lipid species containing linoleic acid (C18:2) were shown to have significantly lower levels in the 0-10 days group with a gradual increase in the 2-18 month, reaching the highest concentrations in the 3-13 year group. The results of this study highlighted the adaptations of the lipid profile at different pediatric ages. These results may help improve understanding of the evolution of lipid metabolism throughout childhood and should be investigated further.

Comprehensive lipidomic profiling by plasma separation cards

Large-scale lipidomic analyses have been limited by the cost and accessibility of traditional venipuncture sampling. Microsampling techniques offer a less-invasive and more accessible alternative. From a single drop of blood, plasma separation cards (PSC) deliver two volumetric dried plasma samples which are studied here for profiling endogenous blood lipids. Six lots of EDTA-treated human whole blood were used to compare PSC, dried blood spot analyses (DBS), and classic wet plasma extractions. Six replicate extractions were performed for each lot. Nontargeted lipidomics was performed by liquid chromatography-high resolution tandem mass spectrometry. Lipids were annotated by accurate mass/retention time matching and MS/MS spectral library matching using peak intensities for quantitation. Four hundred ninety-eight compounds covering 24 lipid subclasses were annotated. Inter-lot repeatability was evaluated by the percent relative standard deviation (%RSD) for each lot, giving median %RSD values across the lots at 14.6% for PSC, 9.3% for DBS, and 8.6% for wet plasma. Strong correlations of lipid peak intensities between wet plasma and PSCs were observed, but less for DBS. Lipid recovery and stability were comparable between the PSC and DBS samples, with roughly 60% of annotated lipids stable at room temperature after 28 days. Overall, PSCs provide a better alternative for quantitative blood lipidomic analyses compared to dried blood spots. However, problems with lipid stability for samples handled and shipped at room temperature are currently unavoidable outside of a clinical setting. Data transferability and comparability to standard plasma is lipid and lipid class dependent.

Lipid profiling analyses from mouse models and human infants

This protocol outlines a translational lipidomic approach to discover lipid biomarkers that could predict morphometric body and histological organ measurements (e.g., weight and adiposity gains) during specific stages of life (e.g., early life). We describe procedures ranging from animal experimentation and histological analyses to downstream analytical steps through lipid profiling, both in mice and humans. This protocol represents a reliable and versatile approach to translate and validate candidate lipid biomarkers from animal models to a human cohort. For complete details on the use and execution of this protocol, please refer to Olga et al. (2021).

Dried blood spots in clinical lipidomics: optimization and recent findings

Dried blood spots (DBS) are being considered as an alternative sampling method of blood collection that can be used in combination with lipidomic and other omic analysis. DBS are successfully used in the clinical context to collect samples for newborn screening for the measurement of specific fatty acid derivatives, such as acylcarnitines, and lipids from whole blood for diagnostic purposes. However, DBS are scarcely used for lipidomic analysis and investigations. Lipidomic studies using DBS are starting to emerge as a powerful method for sampling and storage in clinical lipidomic analysis, but the major research work is being done in the pre- and analytical steps and procedures, and few in clinical applications. This review presents a description of the impact factors and variables that can affect DBS lipidomic analysis, such as the type of DBS card, haematocrit, homogeneity of the blood drop, matrix/chromatographic effects, and the chemical and physical properties of the analyte. Additionally, a brief overview of lipidomic studies using DBS to unveil their application in clinical scenarios is also presented, considering the studies of method development and validation and, to a less extent, for clinical diagnosis using clinical lipidomics. DBS combined with lipidomic approaches proved to be as effective as whole blood samples, achieving high levels of sensitivity and specificity during MS and MS/MS analysis, which could be a useful tool for biomarker identification. Lipidomic profiling using MS/MS platforms enables significant insights into physiological changes, which could be useful in precision medicine.

Advanced Microsamples: Current Applications and Considerations for Mass Spectrometry-Based Metabolic Phenotyping Pipelines

Microsamples are collections usually less than 50 µL, although all devices that we have captured as part of this review do not fit within this definition (as some can perform collections of up to 600 µL); however, they are considered microsamples that can be self-administered. These microsamples have been introduced in pre-clinical, clinical, and research settings to overcome obstacles in sampling via traditional venepuncture. However, venepuncture remains the sampling gold standard for the metabolic phenotyping of blood. This presents several challenges in metabolic phenotyping workflows: accessibility for individuals in rural and remote areas (due to the need for trained personnel), the unamenable nature to frequent sampling protocols in longitudinal research (for its invasive nature), and sample collection difficulty in the young and elderly. Furthermore, venous sample stability may be compromised when the temperate conditions necessary for cold-chain transport are beyond control. Alternatively, research utilising microsamples extends phenotyping possibilities to inborn errors of metabolism, therapeutic drug monitoring, nutrition, as well as sport and anti-doping. Although the application of microsamples in metabolic phenotyping exists, it is still in its infancy, with whole blood being overwhelmingly the primary biofluid collected through the collection method of dried blood spots. Research into the metabolic phenotyping of microsamples is limited; however, with advances in commercially available microsampling devices, common barriers such as volumetric inaccuracies and the ‘haematocrit effect’ in dried blood spot microsampling can be overcome. In this review, we provide an overview of the common uses and workflows for microsampling in metabolic phenotyping research. We discuss the advancements in technologies, highlighting key considerations and remaining knowledge gaps for the employment of microsamples in metabolic phenotyping research. This review supports the translation of research from the ‘bench to the community’.

Liquid extraction surface analysis-mass spectrometry: An advanced and environment-friendly analytical tool in modern analysis

The Liquid Extraction Surface Analysis technique is a new high-throughput instrument for ambient mass spectrometry. The benefits of the Liquid Extraction Surface Analysis-Mass Spectrometry approach are the high throughput screening of samples and the absence of sample preparation. Liquid Extraction Surface Analysis-Mass Spectrometry also consumes less solvent for extraction, making it more environmentally friendly and there is no substrate restriction. It utilizes advanced instrumentation like the use of robotic pipettes, nanoelectrospray systems, electronspray ionization chips which makes it highly efficient. In recent years, Liquid Extraction Surface Analysis-Mass Spectrometry has seen widespread use in a variety of analytical fields including drug metabolite analysis, mapping drug distribution in tissues, protein and lipid characterization etc. In this review, we have summarized the basic working principles of the Liquid Extraction Surface Analysis-Mass Spectrometry approach in detail along with a detailed description of the recently reported applications in the analysis of proteins, lipids, drugs and foods. The investigated analytes along with detection methodologies and significant outcomes of various research reports have been presented with the help of tables. This tool has also been utilized in clinical investigations of biological fluids, fingerprint analysis and authentication of agarwood. This article is protected by copyright. All rights reserved.

Metabolomics in early life and the association with body composition at age 2 years

BACKGROUND AND OBJECTIVES

Early life is a critical window for adiposity programming. Metabolic-profile in early life may reflect this programming and correlate with later life adiposity. We investigated if metabolic-profile at 3 months of age is predictive for body composition at 2 years and if there are differences between boys and girls and between infant feeding types.

METHODS

In 318 healthy term-born infants, we determined body composition with skinfold measurements and abdominal ultrasound at 3 months and 2 years of age. High-throughput-metabolic-profiling was performed on 3-month-blood-samples. Using random-forest-machine-learning-models, we studied if the metabolic-profile at 3 months can predict body composition outcomes at 2 years of age.

RESULTS

Plasma metabolite-profile at 3 months was found to predict body composition at 2 years, based on truncal: peripheral-fat-skinfold-ratio (T:P-ratio), with a predictive value of 75.8%, sensitivity of 100% and specificity of 50%. Predictive value was higher in boys (Q²  = 0.322) than girls (Q²  = 0.117). Of the 15 metabolite variables most strongly associated with T:P-ratio, 11 were also associated with visceral fat at 2 years of age.

CONCLUSION

Several plasma metabolites (LysoPC(22:2), dimethylarginine and others) at 3 months associate with body composition outcome at 2 years. These results highlight the importance of the first months of life for adiposity programming.

Lipid Profiles from Dried Blood Spots Reveal Lipidomic Signatures of Newborns Undergoing Mild Therapeutic Hypothermia after Hypoxic-Ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is associated with perinatal brain injury, which may lead to disability or death. As the brain is a lipid-rich organ, various lipid species can be significantly impacted by HIE and these correlate with specific changes to the lipidomic profile in the circulation. Objective: To investigate the peripheral blood lipidomic signature in dried blood spots (DBS) from newborns with HIE. Using univariate analysis, multivariate analysis and sPLS-DA modelling, we show that newborns with moderate-severe HIE (n = 46) who underwent therapeutic hypothermia (TH) displayed a robust peripheral blood lipidomic signature comprising 29 lipid species in four lipid classes; namely phosphatidylcholine (PC), lysophosphatidylcholine (LPC), triglyceride (TG) and sphingomyelin (SM) when compared with newborns with mild HIE (n = 18). In sPLS-DA modelling, the three most discriminant lipid species were TG 50:3, TG 54:5, and PC 36:5. We report a reduction in plasma TG and SM and an increase in plasma PC and LPC species during the course of TH in newborns with moderate-severe HIE, compared to a single specimen from newborns with mild HIE. These findings may guide the research in nutrition-based intervention strategies after HIE in synergy with TH to enhance neuroprotection.

homeRNA: A Self-Sampling Kit for the Collection of Peripheral Blood and Stabilization of RNA

Gene expression analysis (e.g., targeted gene panels and transcriptomics) from whole blood can elucidate mechanisms of the immune function and aid in the discovery of biomarkers. Conventional venipuncture offers only a small snapshot of our broad immune landscape as immune responses may occur outside of the time and location parameters available for conventional venipuncture. A self-operated method that enables flexible sampling of liquid whole blood coupled with immediate stabilization of cellular RNA is instrumental in facilitating capture and preservation of acute or transient immune fluxes. To this end, we developed homeRNA, a kit for self-collection of peripheral blood (∼0.5 mL) and immediate stabilization of cellular RNA, using the Tasso-SST blood collection device with a specially designed stabilizer tube containing RNAlater. To assess the feasibility of homeRNA for self-collection and stabilization of whole blood RNA, we conducted a pilot study (n = 47 participants) in which we sent homeRNA to participants aged 21-69, located across 10 US states (94% successful blood collections, n = 61/65). Among participants who successfully collected blood, 93% reported no or minimal pain/discomfort using the kit (n = 39/42), and 79% reported very easy/somewhat easy stabilization protocol (n = 33/42). Total RNA yield from the stabilized samples ranged between 0.20 and 5.99 μg (mean = 1.51 μg), and all but one RNA integrity number values were above 7.0 (mean = 8.1), indicating limited RNA degradation. The results from this study demonstrate the self-collection and RNA stabilization of whole blood with homeRNA by participants themselves in their own home.

Clinical lipidomics: realizing the potential of lipid profiling

Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration-assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.

Bridging the Polar and Hydrophobic Metabolome in Single-Run Untargeted Liquid Chromatography-Mass Spectrometry Dried Blood Spot Metabolomics for Clinical Purposes

Dried blood spot (DBS) metabolite analysis is a central tool for the clinic, e.g., newborn screening. Instead of applying multiple analytical methods, a single liquid chromatography-mass spectrometry (LC-MS) method was developed for metabolites spanning from highly polar glucose to hydrophobic long-chain acylcarnitines. For liquid chromatography, a diphenyl column and a multi-linear solvent gradient operated at elevated flow rates allowed for an even-spread resolution of diverse metabolites. Injecting moderate volumes of DBS organic extracts directly, in contrast to evaporation and reconstitution, provided substantial increases in analyte recovery. Q Exactive MS settings were also tailored for sensitivity increases, and the method allowed for analyte retention time and peak area repeatabilities of 0.1-0.4 and 2-10%, respectively, for a wide polarity range of metabolites (log P -4.4 to 8.8). The method's performance was suited for both untargeted analysis and targeted approaches evaluated in clinically relevant experiments.

Comparison of dried blood spot and plasma sampling for untargeted metabolomics

INTRODUCTION

Untargeted metabolomics holds significant promise for biomarker detection and development. In resource-limited settings, a dried blood spot (DBS)-based platform would offer significant advantages over plasma-based approaches that require a cold supply chain.

OBJECTIVES

The primary goal of this study was to compare the ability of DBS- and plasma-based assays to characterize maternal metabolites. Utility of the two assays was also assessed in the context of a case-control predictive model in pregnant women living with HIV.

METHODS

Untargeted metabolomics was performed on archived paired maternal plasma and DBS from n = 79 women enrolled in a large clinical trial.

RESULTS

A total of 984 named biochemicals were detected across both plasma and DBS samples, of which 627 (63.7%), 260 (26.4%), and 97 (9.9%) were detected in both plasma and DBS, plasma alone, and DBS alone, respectively. Variation attributable to study individual (R² = 0.54, p < 0.001) exceeded that of the sample type (R² = 0.21, p < 0.001), suggesting that both plasma and DBS were capable of differentiating individual metabolomic profiles. Log-transformed metabolite abundances were strongly correlated (mean Spearman rho = 0.51) but showed low agreement (mean intraclass correlation of 0.15). However, following standardization, DBS and plasma metabolite profiles were strongly concordant (mean intraclass correlation of 0.52). Random forests classification models for cases versus controls identified distinct feature sets with comparable performance in plasma and DBS (86.5% versus 91.2% mean accuracy, respectively).

CONCLUSION

Maternal plasma and DBS samples yield distinct metabolite profiles highly predictive of the individual subject. In our case study, classification models showed similar performance albeit with distinct feature sets. Appropriate normalization and standardization methods are critical to leverage data from both sample types. Ultimately, the choice of sample type will likely depend on the compounds of interest as well as logistical demands.

Nontargeted mass spectrometry of dried blood spots for interrogation of the human circulating metabolome

Advances in high-resolution, nontargeted mass spectrometry allow for the simultaneous measure of thousands of metabolites in a single biosample. Application of these analytical approaches to population-scale human studies has been limited by the need for resource-intensive blood sample collection, preparation, and storage. Dried blood spotting, a technique developed decades ago for newborn screening, may offer a simple approach to overcome barriers in human blood acquisition and storage. In this study, we find that over 4,400 spectral features across diverse chemical classes may be efficiently and reproducibly extracted and relatively quantified from human dried blood spots using nontargeted metabolomic analysis employing HILIC and reversed-phase liquid chromatography coupled to Orbitrap mass spectrometry. Moreover, over 80% of metabolites were found to be chemically stable in dried blood spots stored at room temperature for up to a week. In direct relation to plasma samples, dried blood spots exhibited comparable representation of the human circulating metabolome, capturing both known and previously uncharacterized metabolites. Dried blood spot approaches provide an opportunity for rapid and facile human biosampling and storage and will enable widespread metabolomics study of populations, particularly in resource-limited areas.

Untargeted Lipidomic Profiling of Dry Blood Spots Using SFC-HRMS

Lipids are essential cellular constituents that have many critical roles in physiological functions. They are notably involved in energy storage and cell signaling as second messengers, and they are major constituents of cell membranes, including lipid rafts. As a consequence, they are implicated in a large number of heterogeneous diseases, such as cancer, diabetes, neurological disorders, and inherited metabolic diseases. Due to the high structural diversity and complexity of lipid species, the presence of isomeric and isobaric lipid species, and their occurrence at a large concentration scale, a complete lipidomic profiling of biological matrices remains challenging, especially in clinical contexts. Using supercritical fluid chromatography coupled with high-resolution mass spectrometry, we have developed and validated an untargeted lipidomic approach to the profiling of plasma and blood. Moreover, we have tested the technique using the Dry Blood Spot (DBS) method and found that it allows for the easy collection of blood for analysis. To develop the method, we performed the optimization of the separation and detection of lipid species on pure standards, reference human plasma (SRM1950), whole blood, and DBS. These analyses allowed an in-house lipid data bank to be built. Using the MS-Dial software, we developed an automatic process for the relative quantification of around 500 lipids species belonging to the 6 main classes of lipids (including phospholipids, sphingolipids, free fatty acids, sterols, and fatty acyl-carnitines). Then, we compared the method using the published data for SRM 1950 and a mouse blood sample, along with another sample of the same blood collected using the DBS method. In this study, we provided a method for blood lipidomic profiling that can be used for the easy sampling of dry blood spots.

Minimally Invasive Biospecimen Collection for Exposome Research in Children's Health

PURPOSE OF REVIEW

The advent of low-volume biosampling and novel biomarker matrices offers non- or minimally invasive approaches to sampling in children. These new technologies, combined with advancements in mass spectrometry that provide high sensitivity, robust measurements of low-concentration exposures, facilitate the application of untargeted metabolomics in children's exposome research. Here, we review emerging sampling technologies for alternative biomatrices-dried capillary blood, interstitial fluid, saliva, teeth, and hair-and highlight recent applications of these samplers to drive discovery in population-based exposure research.

RECENT FINDINGS

Biosampling and biomarker technologies demonstrate potential to directly measure exposures during key developmental time periods. While saliva is the most traditional of the reported biomatrices, each technology has key advantages and disadvantages. For example, hair and teeth provide retrospective analysis of past exposures, and dried capillary blood provides quantitative measurements of systemic exposures that can be more readily compared with traditional venous blood measurements. Importantly, all technologies can or have the potential to be used at home, increasing the convenience and parental support for children's biosampling. This review describes emerging sample collection technologies that hold promise for children's exposome studies. While applications in metabolomics are still limited, these novel matrices are poised to facilitate longitudinal exposome studies to discover key exposures and windows of susceptibility affecting children's health.

Volumetric Absorptive Microsampling of Blood for Untargeted Lipidomics

In the present, proof-of-concept paper, we explore the potential of one common solid support for blood microsampling (dried blood spot, DBS) and a device (volumetric absorptive microsampling, VAMS) developed for the untargeted lipidomic profiling of human whole blood, performed by high-resolution LC-MS/MS. Dried blood microsamples obtained by means of DBS and VAMS were extracted with different solvent compositions and compared with fluid blood to evaluate their efficiency in profiling the lipid chemical space in the most broad way. Although more effort is needed to better characterize this approach, our results indicate that VAMS is a viable option for untargeted studies and its use will bring all the corresponding known advantages in the field of lipidomics, such as haematocrit independence.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

Lipid extraction from dried blood spots and dried milk spots for untargeted high throughput lipidomics

Dried blood spots (DBS) and dried milk spots (DMS) represent convenient matrices for collecting and storing human samples. However, the use of these sample types for researching lipid metabolism remains relatively poorly explored, and especially unclear is the efficiency of lipid extraction in the context of high throughput, untargeted lipidomics. A visual inspection of punched DBSs after standard extraction suggests that the samples remain largely intact. DMSs comprise a dense aggregate of milk fat globules on one side of the card, suggesting that part of the lipid fraction may be physically inaccessible. This led us to the hypothesis that decoagulating may facilitate lipid extraction from both DBSs and DMSs. We tested this hypothesis using a mixture of strong chaeotropes (guanidine and thiourea) in both DBS and DMS in the context of high throughput lipidomics (96/384w plate). Extraction of lipids from DMSs was tested with established extractions and one novel solvent mixture in a high throughput format. We found that exposure of DBSs to chaeotropes facilitated collection of the lipid fraction but was ineffective for DMSs. The lipid fraction of DMSs was best isolated without water, using a mixture of xylene/methanol/isopropanol (1 : 2 : 4). We conclude that decoagulation is essential for efficient extraction of lipids from DBSs and that a non-aqueous procedure using a spectrum of solvents is the best procedure for extracting lipids from DMSs. These methods represent convenient steps that are compatible with the sample structure and type, and with high throughput lipidomics.

Untargeted metabolomics profiling and hemoglobin normalization for archived newborn dried blood spots from a refrigerated biorepository

Archived dried blood spots (DBS) following newborn screening are an attractive resource for interrogating early-life biology using untargeted metabolomics. Therefore, they have the potential to substantially aid etiological studies, particularly for rare and low-frequency childhood diseases and disorders. However, metabolite quantification in DBS is hindered by variation sources not present in serum and plasma samples such as the hematocrit effect and unknown initial blood volumes. Hemoglobin (Hb) is an appropriate correlate for hematocrit in experimentally-generated DBS punches. However, since many biorepositories worldwide archive DBS at 4-5 °C, there is a need to validate the utility of Hb for DBS archived under refrigeration. We evaluated two simple spectroscopic methods for measuring Hb in DBS stored at 4 +/- 2 °C for up to 21 years, obtained from the newborn screening program at the Karolinska University Hospital, Sweden. Spearman correlation analysis and Akaike Information Criterion model selection found that measurement of a Hb sodium lauryl sulfate complex at 540 nm better described nuisance variation than Hb measured at 404 nm, or using age of spot alone. This is the first study to profile metabolites and to propose a normalization factor for metabolite measurements from DBS archived for decades at 4 °C.

Microencapsulated algal feeds as a sustainable replacement diet for broodstock in commercial bivalve aquaculture

The global bivalve shellfish industry makes up 25% of aquaculture, is worth USD $17.2 billion year⁻¹, and relies upon a supply of juvenile bivalves produced by adult broodstock in hatcheries. Today large quantities of live algae are grown to feed broodstock at $220 kg⁻¹, driving highly unsustainable energy and resource use. New advances in algal and microencapsulation technology provide solutions. We developed microencapsulated Schizochytrium algae diets, which can be produced sustainably at < $2 kg⁻¹ from organic side-streams, and are shelf-stable to minimise waste. Physiological, histological, and cutting-edge metabolomic analyses demonstrate that in commercial settings sustainable microencapsulated diets facilitate improved sexual development and 12 × greater omega-3 levels in oysters relative to conventional live algal diets. Every tonne bivalve protein produced instead of fish spares 9 ha, 67 tonnes CO₂, and 40,000 L freshwater. Further research into microencapsulated diets could support bivalve industry expansion, and contribute towards a step-change in sustainable global food production through improved aquaculture practices.

Combining lipidomics and machine learning to measure clinical lipids in dried blood spots

INTRODUCTION

Blood-based sample collection is a challenge, and dried blood spots (DBS) represent an attractive alternative. However, for DBSs to be an alternative to venous blood it is important that these samples are able to deliver comparable associations with clinical outcomes. To explore this we looked to see if lipid profile data could be used to predict the concentration of triglyceride, HDL, LDL and total cholesterol in DBSs using markers identified in plasma.

OBJECTIVES

To determine if DBSs can be used as an alternative to venous blood in both research and clinical settings, and to determine if machine learning could predict 'clinical lipid' concentration from lipid profile data.

METHODS

Lipid profiles were generated from plasma (n = 777) and DBS (n = 835) samples. Random forest was applied to identify and validate panels of lipid markers in plasma, which were translated into the DBS cohort to provide robust measures of the four 'clinical lipids'.

RESULTS

In plasma samples panels of lipid markers were identified that could predict the concentration of the 'clinical lipids' with correlations between estimated and measured triglyceride, HDL, LDL and total cholesterol of 0.920, 0.743, 0.580 and 0.424 respectively. When translated into DBS samples, correlations of 0.836, 0.591, 0.561 and 0.569 were achieved for triglyceride, HDL, LDL and total cholesterol.

CONCLUSION

DBSs represent an alternative to venous blood, however further work is required to improve the combined lipidomics and machine learning approach to develop it for use in health monitoring.

Extraction of Lipids from Liquid Biological Samples for High-Throughput Lipidomics

Extraction of the lipid fraction is a key part of acquiring lipidomics data. High-throughput lipidomics, the extraction of samples in 96w plates that are then run on 96 or 384w plates, has particular requirements that mean special development work is needed to fully optimise an extraction method. Several methods have been published as suitable for it. Here, we test those methods using four liquid matrices: milk, human serum, homogenised mouse liver and homogenised mouse heart. In order to determine the difference in performance of the methods as objectively as possible, we used the number of lipid variables identified, the total signal strength and the coefficient of variance to quantify the performance of the methods. This showed that extraction methods with an aqueous component were generally better than those without for these matrices. However, methods without an aqueous fraction in the extraction were efficient for milk samples. Furthermore, a mixture containing a chlorinated solvent (dichloromethane) appears to be better than an ethereal solvent (tert-butyl methyl ether) for extracting lipids. This study suggests that a 3:1:0.005 mixture of dichloromethane, methanol and triethylammonium chloride, with an aqueous wash, is the most efficient of the currently reported methods for high-throughput lipid extraction and analysis. Further work is required to develop non-aqueous extraction methods that are both convenient and applicable to a broad range of sample types.

Plasma Metabolome Alterations Associated with Extrauterine Growth Restriction

Very preterm infants (VPI, born at or before 32 weeks of gestation) are at risk of adverse health outcomes, from which they might be partially protected with appropriate postnatal nutrition and growth. Metabolic processes or biochemical markers associated to extrauterine growth restriction (EUGR) have not been identified. We applied untargeted metabolomics to plasma samples of VPI with adequate weight for gestational age at birth and with different growth trajectories (29 well-grown, 22 EUGR) at the time of hospital discharge. A multivariate analysis showed significantly higher levels of amino-acids in well-grown patients. Other metabolites were also identified as statistically significant in the comparison between groups. Relevant differences (with corrections for multiple comparison) were found in levels of glycerophospholipids, sphingolipids and other lipids. Levels of many of the biochemical species decreased progressively as the level of growth restriction increased in severity. In conclusion, an untargeted metabolomic approach uncovered previously unknown differences in the levels of a range of plasma metabolites between well grown and EUGR infants at the time of discharge. Our findings open speculation about pathways involved in growth failure in preterm infants and the long-term relevance of this metabolic differences, as well as helping in the definition of potential biomarkers.

Metabolomics and adductomics of newborn bloodspots to retrospectively assess the early-life exposome

PURPOSE OF REVIEW

Exposomics studies can measure health-relevant chemical exposures during a lifetime and estimate the 'internal' environment. However, sampling limitations make these features difficult to capture directly during the critical neonatal time period.

RECENT FINDINGS

We review the use of newborn dried bloodspots (DBS) archived from newborn screening programs for exposomic analysis in epidemiological children's health studies. Emerging 'omics technologies such as adductomics and metabolomics have been adapted for DBS analysis, and these technologies can now provide valuable etiological information on the complex interplay between exposures, biological response, and population phenotypes.

SUMMARY

Adductomics and metabolomics of DBS can provide robust measurements for retrospective epidemiological investigations. With extensive bioarchiving programs in the United States and other countries, DBS are poised to substantially aid epidemiological studies, particularly for rare and low-frequency childhood diseases and disorders.

Improved Dried Blood Spot-Based Metabolomics: A Targeted, Broad-Spectrum, Single-Injection Method

Dried blood spots (DBS) have proven to be a powerful sampling and storage method for newborn screening and many other applications. However, DBS methods have not yet been optimized for broad-spectrum targeted metabolomic analysis. In this study, we developed a robust, DBS-based, broad-spectrum, targeted metabolomic method that was able to measure over 400 metabolites from a 6.3 mm punch from standard Whatman 903^TM filter paper cards. The effects of blood spot volumes, hematocrit, vacutainer chemistry, extraction methods, carryover, and comparability with plasma and fingerstick capillary blood samples were analyzed. The stability of over 400 metabolites stored under varying conditions over one year was also tested. No significant impacts of blood volume and hematocrit variations were observed when the spotted blood volume was over 60 µL and the hematocrit was between 31% and 50%. The median area under the curve (AUC) of metabolites in the DBS metabolome declined by 40% in the first 3 months and then did not decline further for at least 1 year. All originally detectable metabolites remained within detectable limits. The optimal storage conditions for metabolomic analysis were -80 °C with desiccants and without an O₂ scavenger. The method was clinically validated for its potential utility in the diagnosis of the mitochondrial disease mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS). Our method provides a convenient alternative to freezing, storing, and shipping liquid blood samples for comparative metabolomic studies.

Utilization of archived neonatal dried blood spots for genome-wide genotyping

Introduction

Heel pricks are performed on newborns for diagnostic screenings of various pre-symptomatic metabolic and genetic diseases. Excess blood is spotted on Guthrie cards and archived by many states in biobanks for follow-up diagnoses and public health research. However, storage environment may vary across biobanks and across time within biobanks. With increased applications of DNA extracted from spots for genetic studies, identifying factors associated with genotyping success is critical to maximize DNA quality for future studies.

Method

We evaluated 399 blood spots, which were part of a genome-wide association study of childhood leukemia risk in children with Down syndrome, archived at the Michigan Neonatal Biobank between 1992 and 2008. High quality DNA was defined as having post-quality control call rate ≥ 99.0% based on the Illumina GenomeStudio 2.0 GenCall algorithm after processing the samples on the Illumina Infinium Global Screening Array. Bivariate analyses and multivariable logistic regression models were applied to evaluate effects of storage environment and storage duration on DNA genotyping quality.

Results

Both storage environment and duration were associated with sample genotyping call rates (p-values < 0.001). Sample call rates were associated with storage duration independent of storage environment (p-trend = 0.006 for DBS archived in an uncontrolled environment and p-trend = 0.002 in a controlled environment). However, 95% of the total sample had high genotyping quality with a call rate ≥ 95.0%, a standard threshold for acceptable sample quality in many genetic studies.

Conclusion

Blood spot DNA quality was lower in samples archived in uncontrolled storage environments and for samples archived for longer durations. Still, regardless of storage environment or duration, neonatal biobanks including the Michigan Neonatal Biobanks can provide access to large collections of spots with DNA quality acceptable for most genotyping studies.

A high-throughput platform for detailed lipidomic analysis of a range of mouse and human tissues

Lipidomics is of increasing interest in studies of biological systems. However, high-throughput data collection and processing remains non-trivial, making assessment of phenotypes difficult. We describe a platform for surveying the lipid fraction for a range of tissues. These techniques are demonstrated on a set of seven different tissues (serum, brain, heart, kidney, adipose, liver, and vastus lateralis muscle) from post-weaning mouse dams that were either obese (> 12 g fat mass) or lean (<5 g fat mass). This showed that the lipid metabolism in some tissues is affected more by obesity than others. Analysis of human serum (healthy non-pregnant women and pregnant women at 28 weeks' gestation) showed that the abundance of several phospholipids differed between groups. Human placenta from mothers with high and low BMI showed that lean placentae contain less polyunsaturated lipid. This platform offers a way to map lipid metabolism with immediate application in metabolic research and elsewhere. Graphical abstract.

Altered triglyceride and phospholipid metabolism predates the diagnosis of gestational diabetes in obese pregnancy

Gestational diabetes (GDM), a common pregnancy complication associated with obesity and long-term health risks, is usually diagnosed at approximately 28 weeks of gestation. An understanding of lipid metabolism in women at risk of GDM could contribute to earlier diagnosis and treatment. We tested the hypothesis that altered lipid metabolism at the beginning of the second trimester in obese pregnant women is associated with a diagnosis of GDM. Plasma samples from 831 participants (16-45 years, 15-18 weeks gestation, BMI ≥ 30) from the UPBEAT study of obese pregnant women were used. The lipid, sterol and glyceride fraction was isolated and analysed in a semi-quantitative fashion using direct infusion mass spectrometry. A combination of uni-, multi-variate and multi-variable statistical analyses was used to identify candidate biomarkers in plasma associated with a diagnosis of GDM (early third trimester; IADPSG criteria). Multivariable adjusted analyses showed that participants who later developed GDM had a greater abundance of several triglycerides (48:0, 50:1, 50:2, 51:5, 53:4) and phosphatidylcholine (38:5). In contrast sphingomyelins (32:1, 41:2, 42:3), lyso-phosphatidylcholine (16:0, 18:1), phosphatidylcholines (35:2, 40:7, 40:10), two polyunsaturated triglycerides (46:5, 48:6) and several oxidised triglycerides (48:6, 54:4, 56:4, 58:6) were less abundant. We concluded that both lipid and triglyceride metabolism were altered at least 10 weeks before diagnosis of GDM. Further investigation is required to determine the functional consequences of these differences and the mechanisms by which they arise.

Investigation of the 12-Month Stability of Dried Blood and Urine Spots Applying Untargeted UHPLC-MS Metabolomic Assays

The use of dried blood spot (DBS) and dried urine spot (DUS) samples represents an attractive opportunity for researchers in biomedical metabolomics to collect whole blood and urine samples in the absence of a processing laboratory and so to allow collection in remote areas or in longitudinal studies away from the clinic. The 12-month stability of the thousands of metabolites present in these biofluids and the applicability of DBS and DUS samples for untargeted metabolomics applications has not previously been investigated in detail and compared to blood and urine samples. Here, the 12-month stability of DBS and DUS at different storage temperatures (-20, +4, and +21 °C) have been compared to plasma and urine biofluids stored at the same storage temperatures and time. Samples were analyzed applying complementary HILIC and C₁₈ reversed-phase UHPLC-MS untargeted metabolomic assays. Results show that metabolites demonstrate increased stability in DBS and DUS compared to whole blood and urine at all storage temperatures and times. DBS and DUS stored at +21 °C are stable for up to 4 weeks but are not stable over a 1 year period. DBS and DUS showed good stability when stored at -20 °C for 1 year. We recommend that DBS and DUS samples are collected and transported within 28 days at room temperature and are stored for longer periods of time at -20 or -80 °C. The metabolomes of DUS samples and urine were very similar but the metabolome of DBS included additional metabolites not detected in plasma and therefore proposed to be released from cells in whole blood.

Inborn Errors of Metabolism in the Era of Untargeted Metabolomics and Lipidomics

Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways by genetic mutations, either directly or indirectly by cofactor deficiencies, causing altered levels of compounds associated with these pathways. While IEMs may present with multiple overlapping symptoms and metabolites, early and accurate diagnosis of IEMs is critical for the long-term health of affected subjects. The prevalence of IEMs differs between countries, likely because different IEM classifications and IEM screening methods are used. Currently, newborn screening programs exclusively use targeted metabolic assays that focus on limited panels of compounds for selected IEM diseases. Such targeted approaches face the problem of false negative and false positive diagnoses that could be overcome if metabolic screening adopted analyses of a broader range of analytes. Hence, we here review the prospects of using untargeted metabolomics for IEM screening. Untargeted metabolomics and lipidomics do not rely on predefined target lists and can detect as many metabolites as possible in a sample, allowing to screen for many metabolic pathways simultaneously. Examples are given for nontargeted analyses of IEMs, and prospects and limitations of different metabolomics methods are discussed. We conclude that dedicated studies are needed to compare accuracy and robustness of targeted and untargeted methods with respect to widening the scope of IEM diagnostics.

Evidence from 3-month-old infants shows that a combination of postnatal feeding and exposures in utero shape lipid metabolism

We tested the hypothesis that both postnatal feeding and conditions in utero affect lipid metabolism in infants. Infants who experienced restrictive growth conditions in utero and others exposed to maternal hyperglycaemia were compared to a control group with respect to feeding mode. Dried blood spots were collected from a pilot subset of infant participants of the Cambridge Baby Growth Study at 3mo. Groups: (a) a normal gestation (control, n = 40), (b) small for gestational age (SGA, n = 34) and (c) whose mothers developed hyperglycaemia (n = 59). These groups were further stratified by feeding mode; breastfed, formula-fed or received a mixed intake. Their phospholipid, glyceride and sterol fractions were profiled using direct infusion mass spectrometry. Statistical tests were used to identify molecular species that indicated differences in lipid metabolism. The abundance of several phospholipids identified by multivariate analysis, PC(34:1), PC(34:2) and PC-O(34:1), was 30-100% higher across all experimental groups. SM(39:1) was around half as abundant in in utero groups among breastfed infants only. The evidence from this pilot study shows that phospholipid metabolism is modulated by both conditions in utero and postnatal feeding in a cohort of 133 Caucasian infants, three months post partum.

Relationship between the lipid composition of maternal plasma and infant plasma through breast milk

INTRODUCTION

This study was motivated by the report that infant development correlates with particular lipids in infant plasma.

OBJECTIVE

The hypothesis was that the abundance of these candidate biomarkers is influenced by the dietary intake of the infant.

METHODS

A cohort of 30 exclusively-breastfeeding mother-infant pairs from a small region of West Africa was used for this observational study. Plasma and milk from the mother and plasma from her infant were collected within 24 h, 3 months post partum. The lipid, sterol and glyceride composition was surveyed using direct infusion MS in positive and negative ion modes. Analysis employed a combination of univariate and multivariate tests.

RESULTS

The lipid profiles of mother and infant plasma samples are similar but distinguishable, and both are distinct from milk. Phosphatidylcholines (PC), cholesteryl esters (CEs) and cholesterol were more abundant in mothers with respect to their infants, e.g. PC(34:1) was 5.66% in mothers but 3.61% in infants (p = 3.60 × 10^-10), CE(18:2) was 8.05% in mothers but 5.18% in infants (p = 1.37 × 10^-11) whilst TGs were lower in mothers with respect to their infants, e.g. TG(52:2) was 2.74% in mothers and 4.23% in infants (p = 1.63 × 10^-05). A latent structure model showed that four lipids in infant plasma previously shown to be biomarkers clustered with cholesteryl esters in the maternal circulation.

CONCLUSION

This study found evidence that the abundance of individual lipid isoforms associated with infant development are associated with the abundance of individual molecular species in the mother's circulation.

Rapid profiling of triglycerides in human breast milk using liquid extraction surface analysis Fourier transform mass spectrometry reveals new very long chain fatty acids and differences within individuals

RATIONALE

We describe a novel method for preparing milk samples and profiling their triglyceride (TG) fractions. This method was used to explore how the TG profile of milk modulates as lactation progresses and how the TG profile differs between breasts.

METHODS

Fresh milk was spotted onto Whatman filter paper and air-dried. Liquid Extraction Surface Analysis coupled to Fourier Transform Mass Spectrometry (LESA-MS) was adapted for molecular profiling. Collision-Induced Dissociation (CID) was used to profile fatty acid residues.

RESULTS

LESA-MS produced the relative abundances of all isobaric TGs described and showed that mammary glands within one individual can produce a different profile of TGs. CID was used to uncover the configuration of isobaric triglycerides, indicating the relative amounts of the fatty acids contributing to that triglyceride's mass. This also indicated the presence of very long chain fatty acids (C26:0 and C26:1) that have not been reported before in human breast milk.

CONCLUSIONS

We conclude that spotting on paper and the use of LESA-MS and CID on milk spots is not only a means for analysing milk in unprecedented detail for this preparation time, but is also amenable to conditions in which collecting and storing fresh milk samples for detailed profiling is prohibitively difficult.

The Lipid and Glyceride Profiles of Infant Formula Differ by Manufacturer, Region and Date Sold

We tested the hypothesis that the lipid composition of infant formula is consistent between manufacturers, countries and target demographic. We developed techniques to profile the lipid and glyceride fraction of milk and formula in a high throughput fashion. Formula from principal brands in the UK (2017-2019; bovine-, caprine-, soya-based), the Netherlands (2018; bovine-based) and South Africa (2018; bovine-based) were profiled along with fresh British animal and soya milk and skimmed milk powder. We found that the lipid and glyceride composition of infant formula differed by region, manufacturer and date of manufacture. The formulations within some brands, aimed at different target age ranges, differed considerably where others were similar across the range. Soya lecithin and milk lipids had characteristic phospholipid profiles. Particular sources of fat, such as coconut oil, were also easy to distinguish. Docosahexaenoic acid is typically found in triglycerides rather than phospholipids in formula. The variety by region, manufacturer, date of manufacture and sub-type for target demographics lead to an array of lipid profiles in formula. This makes it impossible to predict its molecular profile. Without detailed profile of the formula fed to infants, it is difficult to characterise the relationship between infant nutrition and their growth and development.

Direct Infusion Based Metabolomics Identifies Metabolic Disease in Patients' Dried Blood Spots and Plasma

In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire a complete view of metabolite status. Here, we describe a non-quantitative direct-infusion high-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method for both dried blood spots (DBS) and plasma. 110 DBS of 42 patients harboring 23 different inborn errors of metabolism (IEM) and 86 plasma samples of 38 patients harboring 21 different IEM were analyzed using DI-HRMS. A peak calling pipeline developed in R programming language provided Z-scores for ~1875 mass peaks corresponding to ~3835 metabolite annotations (including isomers) per sample. Based on metabolite Z-scores, patients were assigned a ‘most probable diagnosis’ by an investigator blinded for the known diagnoses of the patients. Based on DBS sample analysis, 37/42 of the patients, corresponding to 22/23 IEM, could be correctly assigned a ‘most probable diagnosis’. Plasma sample analysis, resulted in a correct ‘most probable diagnosis’ in 32/38 of the patients, corresponding to 19/21 IEM. The added clinical value of the method was illustrated by a case wherein DI-HRMS metabolomics aided interpretation of a variant of unknown significance (VUS) identified by whole-exome sequencing. In summary, non-quantitative DI-HRMS metabolomics in DBS and plasma is a very consistent, high-throughput and nonselective method for investigating the metabolome in genetic disease.

Associations between the maternal circulating lipid profile in pregnancy and fetal imprinted gene alleles: a cohort study

BACKGROUND

Imprinted genes, which are expressed in a parent of origin-specific manner, are thought to mediate the genetic priorities of each parent in pregnancy. Recently we reported that some fetal imprinted gene variants are associated with maternal glucose concentrations and blood pressures in pregnancy. We suggest that the conflict between the effects of paternal and maternal transmitted genes starts at conception and may already be evident in measures of maternal metabolism in early pregnancy, before gestational diabetes is manifest.

METHODS

Lipid fractions in maternal non-fasting serum collected around week 15 of pregnancy were profiled using direct infusion mass spectrometry in a subset Discovery Cohort (n = 200) of women from the Cambridge Baby Growth Study using direct infusion mass spectrometry. Associations between 151 haplotype-tag fetal polymorphisms in 16 imprinted genes and lipids were determined using partial least squares discriminant analysis. Variable importance in projection scores were used to identify those lipid species that contribute most to the underlying variation in the lipid profile and the concentrations of these species tested for associations with fetal imprinted gene alleles using linear regression. In an internal Validation Cohort (n = 567 women from the same cohort) the lipid fraction was profiled using liquid chromatography-mass spectrometry and tested for associations with the same fetal imprinted gene variants as above, followed by meta-analysis of associations from the Discovery and Validation Cohorts.

RESULTS

The most significant associations were between a monounsaturated triglyceride (44:1) and both paternally-transmitted fetal H19 rs7950932 (R = 0.14, p = 2.9 × 10^- 3, n = 386) and maternally-transmitted fetal FAM99A rs7131362 (R = 0.18, p = 6.2 × 10^- 3, n = 351; association with maternal-untransmitted allele R = 0.08, p = 0.07, n = 328). This same triglyceride isoform was also associated with subsequent week 28 fasting glucose concentrations (R = 0.09, p = 9.9 × 10^- 3, n = 673) and homeostasis model assessment of insulin resistance (R = 0.09, p = 0.01, n = 664).

CONCLUSIONS

Fetal imprinted genes may influence maternal circulating clinically relevant triglyceride concentrations early in pregnancy.

The validation of biomarkers of metabolic efficacy in infant nutrition

Breastfeeding is regarded as the ideal way to nourish infants. However, feeding with formula milk is also common in much of the West. Despite this, the function of the molecular components of breast and formula milks are not fully understood, less still the relationship between the composition of the milk and the infant's metabolism and how this influences the infant's development. The Biotechnology and Biological Sciences Research Council-funded project 'The validation of biomarkers of metabolic efficacy in infant nutrition' aims to identify lipid biomarkers that can be used to study the effect of diet on growth and development of infants. In this work, we have been able to validate these markers. Here, we present an approach to biomarker discovery that has new depth and will inform research questions about how metabolism is governed, and which species can be used to identify situations where metabolism is becoming defective.