Metabonomics of Newborn Screening Dried Blood Spot Samples: A Novel Approach in the Screening and Diagnostics of Inborn Errors of Metabolism

Multimodal Metabolomic Analysis Reveals Novel Metabolic Disturbances in Adults With Early Treated Phenylketonuria

Phenylketonuria (PKU) is an inborn error of metabolism responsible for an accumulation of phenylalanine, which leads to cognitive and developmental disorders if left untreated. Most studies of adult PKU focus on neuropsychiatric complications, but new questions have been raised about systemic manifestations of PKU in adulthood. Fifteen adults with classic PKU with poor metabolic control and 15 matched healthy controls were recruited to compare their blood metabolomes by an untargeted multimodal approach (polar, apolar, and lipids) by LC/MS and a targeted approach to the tryptophan pathway. Targeted analysis revealed systemic serotonin hypometabolism and aberrant kynurenine metabolism, as well as potential implication of microbiota by differences in some indole compounds compared to controls. Untargeted analysis confirms previous findings regarding the TCA cycle, alanine aspartate glutamate metabolism, arginine and proline metabolism, and revealed some new metabolic perturbations such as arginine biosynthesis or glyoxylate and dicarboxylate metabolism. Future studies involving larger numbers of patients with varying degrees of metabolic control are needed to confirm these findings.

The Multi-Omic Approach to Newborn Screening: Opportunities and Challenges

Newborn screening programs have seen significant evolution since their initial implementation more than 60 years ago, with the primary goal of detecting treatable conditions within the earliest possible timeframe to ensure the optimal treatment and outcomes for the newborn. New technologies have driven the expansion of screening programs to cover additional conditions. In the current era, the breadth of screened conditions could be further expanded by integrating omic technologies such as untargeted metabolomics and genomics. Genomic screening could offer opportunities for lifelong care beyond the newborn period. For genomic newborn screening to be effective and ready for routine adoption, it must overcome barriers such as implementation cost, public acceptability, and scalability. Metabolomics approaches, on the other hand, can offer insight into disease phenotypes and could be used to identify known and novel biomarkers of disease. Given recent advances in metabolomic technologies, alongside advances in genomics including whole-genome sequencing, the combination of complementary multi-omic approaches may provide an exciting opportunity to leverage the best of both approaches and overcome their respective limitations. These techniques are described, along with the current outlook on multi-omic-based NBS research.

Determination of amino acid metabolic diseases from dried blood spots with a rapid extraction method coupled with nanoelectrospray ionization mass spectrometry

In this work, a rapid extraction method of methanol/water (95:5 v/v) with 0.1% formic acid was developed for extraction of amino acids from dried blood spots (DBS) for inherited metabolic diseases (IMDs). The combination of this extraction procedure with nanoelectrospray ionization mass spectrometry (nESI-MS) was used for the rapid analysis of amino acids. This approach with eliminating the chromatographic separation required only 2 min for the extraction of amino acids from DBS, which simplified the configuration and improved the timeliness. Dependence of the sensitivity on the operating parameters was systematically investigated. The LOD of 91.2-262.5 nmol/L and LOQ of 304-875 nmol/L which were lower than the cut-off values were obtained for amino acids within DBS. The accuracy was determined to be 93.82%-103.07% and the precision was determined to be less than 8.30%. The effectiveness of this method was also compared with the gold standard method (e.g., LC-MS/MS). The desalination mechanism was explored with interference mainly originated from the blood. These findings indicated that the rapid extraction procedure coupled with nESI-MS is capable of screening indicators for IMDs in complex biological samples.

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.

VAMS-Based Blood Capillary Sampling for Mass Spectrometry-Based Human Metabolomics Studies

Volumetric absorptive microsampling (VAMS) is a recently developed sample collection method that enables single-drop blood collection in a minimally invasive manner. Blood biomolecules can then be extracted and processed for analysis using several analytical platforms. The integration of VAMS with conventional mass spectrometry (MS)-based metabolomics approaches is an attractive solution for human studies representing a less-invasive procedure compared to phlebotomy with the additional potential for remote sample collection. However, as we recently demonstrated, VAMS samples require long-term storage at -80 °C. This study investigated the stability of VAMS samples during short-term storage and compared the metabolome obtained from capillary blood collected from the fingertip to those of plasma and venous blood from 22 healthy volunteers. Our results suggest that the blood metabolome collected by VAMS samples is stable at room temperature only for up to 6 h requiring subsequent storage at -80 °C to avoid significant changes in the metabolome. We also demonstrated that capillary blood provides better coverage of the metabolome compared to plasma enabling the analysis of several intracellular metabolites presented in red blood cells. Finally, this work demonstrates that with the appropriate pre-analytical protocol capillary blood can be successfully used for untargeted metabolomics studies.

[The promise of omics in the precision medicine era]

The rise of omics technologies that simultaneously measure thousands of molecules in a complex biological sample represents the core of systems biology. These technologies have profoundly impacted biomarkers and therapeutic targets discovery in the precision medicine era. Systems biology aims to perform a systematic probing of complex interactions in biological systems. Powered by high-throughput omics technologies and high-performance computing, systems biology provides relevant, resolving, and multi-scale overviews from cells to populations. Precision medicine takes advantage of these conceptual and technological developments and is based on two main pillars: the generation of multimodal data and their subsequent modeling. High-throughput omics technologies enable the comprehensive and holistic extraction of biological information, while computational capabilities enable multidimensional modeling and, as a result, offer an intuitive and intelligible visualization. Despite their promise, translating these technologies into clinically actionable tools has been slow. In this contribution, we present the most recent multi-omics data generation and analysis strategies and their clinical deployment in the post-genomic era. Furthermore, medical application challenges of omics-based biomarkers are discussed.

Identification and characterization of post-translational modifications: Clinical implications

Post-translational modifications (PTMs) generate marginally modified isoforms of native peptides, proteins and lipoproteins thereby regulating protein functions, molecular interactions, and localization. With a key role in functional proteomics, post-translational modifications are recently also associated with the onsets and progressions of various diseases, such as cancer, cardiovascular, renal, and metabolic diseases. With the impact of post-translational modifications becoming increasingly clear, its reliable detection and quantification remain a major obstacle in the translation of these novel pathological markers into clinical diagnosis. While current antibody-based clinical diagnostics struggle to detect and quantify these marginal protein and lipoprotein alterations, state-of-the-art mass spectrometric, proteomic approaches provide the mass accuracy and resolving power necessary to isolate, identify and quantify novel and pathological post-translational modifications; however clinical translation of mass spectrometric applications are still facing major challenges. Here we review the status quo of the clinical translation of mass-spectrometric applications as novel diagnostic tools for the identification and quantification of post-translational modifications and focus on the emerging role of mass spectrometric methods in the clinical assessment of PTMs in disease states.

Profiling Tryptophan Catabolites of Human Gut Microbiota and Acute-Phase Protein Levels in Neonatal Dried Blood Specimens

National screening programs use dried blood specimens to detect metabolic disorders or aberrant protein functions that are not clinically evident in the neonatal period. Similarly, gut microbiota metabolites and immunological acute-phase proteins may reveal latent immune aberrations. Microbial metabolites interact with xenobiotic receptors (i.e., aryl hydrocarbon and pregnane-X) to maintain gastrointestinal tissue health, supported by acute-phase proteins, functioning as sensors of microbial immunomodulation and homeostasis. The delivery (vaginal or cesarean section) shapes the microbial colonization, which substantially modulates both the immune system’s response and mucosal homeostasis. This study profiled microbial metabolites of the kynurenine and tryptophan pathway and acute-phase proteins in 134 neonatal dried blood specimens. We newly established neonatal blood levels of microbial xenobiotic receptors ligands (i.e., indole-3-aldehyde, indole-3-butyric acid, and indole-3-acetamide) on the second day of life. Furthermore, we observed diverse microbial metabolic profiles in neonates born vaginally and via cesarean section, potentially due to microbial immunomodulatory influence. In summary, these findings suggest the supportive role of human gut microbiota in developing and maintaining immune system homeostasis.

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.

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.

A feasibility study of metabolic phenotyping of dried blood spot specimens in rural Chinese women exposed to household air pollution

BACKGROUND

Exposure-response studies and policy evaluations of household air pollution (HAP) are limited by current methods of exposure assessment which are expensive and burdensome to participants.

METHODS

We collected 152 dried blood spot (DBS) specimens during the heating and non-heating seasons from 53 women who regularly used biomass-burning stoves for cooking and heating. Participants were enrolled in a longitudinal study in China. Untargeted metabolic phenotyping of DBS were generated using ultra-high performance liquid chromatography coupled with mass spectrometry to exemplify measurement precision and assessment for feasibility to detect exposure to HAP, evaluated by season (high pollution vs. low pollution) and measured personal exposure to fine particulate matter <2.5 μm diameters (PM2.5) and black carbon (BC) in the 48-h prior to collecting the DBS specimen.

RESULTS

Metabolites e.g., amino acids, acyl-carnitines, lyso-phosphorylcholines, sphinganine, and choline were detected in the DBS specimens. Our approach is capable of detecting the differences in personal exposure to HAP whilst showing high analytical reproducibility, coefficient of variance (CV) <15%, meeting the U.S. Food and Drug Administration criteria.

CONCLUSIONS

Our results provide a proof of principle that high-resolution metabolic phenotypic data can be generated using a simple DBS extraction method thus suitable for exposure studies in remote, low-resource settings where the collection of serum and plasma is logistically challenging or infeasible. The analytical run time (19 min/specimen) is similar to most global phenotyping methods and therefore suitable for large-scale application.

Little to Give, Much to Gain-What Can You Do With a Dried Blood Spot?

PURPOSE OF REVIEW

Technological advances have allowed dried blood spots (DBS) to be utilized for various measurements, helpful in population-based studies. The following is a review of the literature highlighting the advantages and disadvantages of DBS and describing their use in multiple areas of research.

RECENT FINDINGS

DBS can track pollutant exposure to understand their impact on health. DBS can also be used for (epi-)genetic studies, to measure clinical biomarkers, and to monitor drug adherence. Advantages of DBS include being minimally invasive, requiring low blood volume, and being cost-effective to collect, transport, and store. Disadvantages of DBS include the hematocrit effect, which is related to the viscosity of the blood affecting its spread on to the filter paper, causing a major source of error when assessing concentrations, and the possibility of low DNA volume. Numerous uses for DBS make them an important source of biomaterial but they require additional validation for accuracy and reproducibility.

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.

High resolution mass spectrometry newborn screening applications for quantitative analysis of amino acids and acylcarnitines from dried blood spots

Amino acid and acylcarnitine first-tier newborn screening typically employs derivatized or non-derivatized sample preparation methods followed by FIA coupled to triple quadrupole (TQ) MS/MS. The low resolving power of TQ instruments results in difficulties distinguishing nominal isobaric metabolites, especially those with identical quantifying product ions such as malonylcarnitine (C3DC) and 4-hydroxybutylcarnitine (C4OH). Twenty-eight amino acids and acylcarnitines extracted from dried blood spots (DBS) were analyzed by direct injection (DI)-HRMS on a Q-Exactive Plus across available mass resolving powers in SIM, in PRM at 17,000 full width at half maximum (FWHM), and a developed SIM/PRM hybrid MS method. Most notably, quantitation of C3DC and C4OH was successful by HRMS in non-derivatized samples, thus, potentially eliminating sample derivatization requirements. Quantitation differed between SIM and PRM acquired data for several metabolites, and it was determined these quantitative differences were due to collision energy differences or kinetic isotope effects between the unlabeled metabolites and the corresponding labeled isotopologue internal standards. Overall quantitative data acquired by HRMS were similar to data acquired on TQ MS/MS platform. A proof-of-concept hybrid DI-HRMS and SIM/PRM/FullScan method was developed demonstrating the ability to hybridize targeted newborn screening with metabolomic screening.

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.

Prediction of VLCAD deficiency phenotype by a metabolic fingerprint in newborn screening bloodspots

PURPOSE

Newborns who test positive for very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) in newborn screening may have a severe phenotype with early onset of life-threatening symptoms but may also have an attenuated phenotype and never become symptomatic. The objective of this study is to investigate whether metabolomic profiles in dried bloodspots (DBS) of newborns allow early phenotypic prediction, permitting tailored treatment and follow-up.

METHODS

A metabolic fingerprint was generated by direct infusion high resolution mass spectrometry in DBS of VLCADD patients (n = 15) and matched controls. Multivariate analysis of the metabolomic profiles was applied to differentiate subgroups.

RESULTS

Concentration of six acylcarnitine species differed significantly between patients and controls. The concentration of C18:2- and C20:0-carnitine, 13,14-dihydroretinol and deoxycytidine monophosphate allowed separation between mild and severe patients. Two patients who could not be prognosticated on early clinical symptoms, were correctly fitted for severity in the score plot based on the untargeted metabolomics.

CONCLUSION

Distinctive metabolomic profiles in DBS of newborns with VLCADD may allow phenotypic prognostication. The full potential of this approach as well as the underlying biochemical mechanisms need further investigation.

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.

NMR-based newborn urine screening for optimized detection of inherited errors of metabolism

Inborn errors of metabolism (IEMs) are rare diseases produced by the accumulation of abnormal amounts of metabolites, toxic to the newborn. When not detected on time, they can lead to irreversible physiological and psychological sequels or even demise. Metabolomics has emerged as an efficient and powerful tool for IEM detection in newborns, children, and adults with late onset. In here, we screened urine samples from a large set of neonates (470 individuals) from a homogeneous population (Basque Country), for the identification of congenital metabolic diseases using NMR spectroscopy. Absolute quantification allowed to derive a probability function for up to 66 metabolites that adequately describes their normal concentration ranges in newborns from the Basque Country. The absence of another 84 metabolites, considered abnormal, was routinely verified in the healthy newborn population and confirmed for all but 2 samples, of which one showed toxic concentrations of metabolites associated to ketosis and the other one a high trimethylamine concentration that strongly suggested an episode of trimethylaminuria. Thus, a non-invasive and readily accessible urine sample contains enough information to assess the potential existence of a substantial number (>70) of IEMs in newborns, using a single, automated and standardized ¹H- NMR-based analysis.

Personalized laboratory medicine: a patient-centered future approach

In contrast to population-based medical decision making, which emphasizes the use of evidence-based treatment strategies for groups of patients, personalized medicine is based on optimizing treatment at the level of the individual patient. The creation of molecular profiles of individual patients was made possible by the advent of "omics" technologies, based on high throughput instrumental techniques in combination with biostatistics tools and artificial intelligence. The goal of personalized laboratory medicine is to use advanced technologies in the process of preventive, curative or palliative patient management. Personalized medicine does not rely on changes in concentration of a single molecular marker to make a therapeutic decision, but rather on changes of a profile of markers characterizing an individual patient's status, taking into account not only the expected response to treatment of the disease but also the expected response of the patient. Such medical approach promises a more effective diagnostics with more effective and safer treatment, as well as faster recovery and restoration of health and improved cost effectiveness. The laboratory medicine profession is aware of its key role in personalized medicine, but to empower the laboratories, at least an enhancement in cooperation between disciplines within laboratory medicine will be necessary.

Biomarkers of Nutrition and Health: New Tools for New Approaches

A main challenge in nutritional studies is the valid and reliable assessment of food intake, as well as its effects on the body. Generally, food intake measurement is based on self-reported dietary intake questionnaires, which have inherent limitations. They can be overcome by the use of biomarkers, capable of objectively assessing food consumption without the bias of self-reported dietary assessment. Another major goal is to determine the biological effects of foods and their impact on health. Systems analysis of dynamic responses may help to identify biomarkers indicative of intake and effects on the body at the same time, possibly in relation to individuals' health/disease states. Such biomarkers could be used to quantify intake and validate intake questionnaires, analyse physiological or pathological responses to certain food components or diets, identify persons with specific dietary deficiency, provide information on inter-individual variations or help to formulate personalized dietary recommendations to achieve optimal health for particular phenotypes, currently referred as "precision nutrition." In this regard, holistic approaches using global analysis methods (omics approaches), capable of gathering high amounts of data, appear to be very useful to identify new biomarkers and to enhance our understanding of the role of food in health and disease.

Direct-infusion based metabolomics unveils biochemical profiles of inborn errors of metabolism in cerebrospinal fluid

BACKGROUND

For inborn errors of metabolism (IEM), metabolomics is performed for three main purposes: 1) development of next generation metabolic screening platforms, 2) identification of new biomarkers in predefined patient cohorts and 3) for identification of new IEM. To date, plasma, urine and dried blood spots are used. We anticipate that cerebrospinal fluid (CSF) holds additional - valuable - information, especially for IEM with neurological involvement. To expand metabolomics to CSF, we here tested whether direct-infusion high-resolution mass spectrometry (DI-HRMS) based non-quantitative metabolomics could correctly capture the biochemical profile of patients with an IEM in CSF.

METHODS

Eleven patient samples, harboring eight different IEM, and thirty control samples were analyzed using DI-HRMS. First we assessed whether the biochemical profile of the control samples represented the expected profile in CSF. Next, each patient sample was assigned a 'most probable diagnosis' by an investigator blinded for the known diagnoses of the patients.

RESULTS

the biochemical profile identified using DI-HRMS in CSF samples resembled the known profile, with - among others - the highest median intensities for mass peaks annotated with glucose, lactic acid, citric acid and glutamine. Subsequent analysis of patient CSF profiles resulted in correct 'most probable diagnoses' for all eleven patients, including non-ketotic hyperglycinaemia, propionic aciduria, purine nucleoside phosphorylase deficiency, argininosuccinic aciduria, tyrosinaemia type I, hyperphenylalaninemia and hypermethioninaemia.

CONCLUSION

We here demonstrate that DI-HRMS based non-quantitative metabolomics accurately captures the biochemical profile of this set of patients in CSF, opening new ways for using metabolomics in CSF in the metabolic diagnostic laboratory.

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.

Analysis of Inflammatory Mediators in Newborn Dried Blood Spot Samples by Chip-Based Immunoaffinity Capillary Electrophoresis

A chip-based immunoaffinity capillary electrophoresis (ICE) system has been developed for measuring inflammatory mediators in dried blood samples routinely taken from newborn babies. A defined area of each dried blood spot was removed from the sample card and its contents eluted. The recovered eluates were injected into the chip and the analytes of interest isolated by the immunoaffinity disk within the chip. The captured analytes were labeled in-situ with a red light-emitting laser dye and electro-eluted into the chip separation channel. Electrophoretic separation of all of the analytes was achieved within 2.0 min with quantification of each peak being performed by online LIF detection and integration of each peak area. The degree of accuracy and precision achieved by the chip-based system is comparable to conventional immunoassays and the system is robust enough to be applied to the analysis of clinical samples.

Liquid extraction surface analysis nanospray electrospray ionization based lipidomics for in situ analysis of tumor cells with multidrug resistance

RATIONALE

Multidrug resistance (MDR) occurs frequently and is a major challenge in tumor treatment. The lipid composition in the cell membrane and the redox balance are closely associated with the development of MDR. Liquid extraction surface analysis in combination with mass spectrometry (LESA-MS) has the characteristics of minimal sample preparation, rapid analysis, high sensitivity and high throughput, and has obtained wide applications.

METHODS

LESA-MS was employed to in situ determine the lipids and other specific metabolites of intact MCF-7/ADR cells (adriamycin-resistant breast cancer cells) and its parental MCF-7/S cells grown on a glass slide. In situ atomic force microscopy was used to observe the morphology of tumor cells before and after extraction. Multivariate statistical analysis was used to investigate the potential lipid biomarkers correlated with the MDR. Moreover, the cell membrane fluidity and potential were determined.

RESULTS

The changes in the level of the lipids were closely correlated with the multidrug resistance of MCF-7/S cells. Moreover, lower cell membrane fluidity and higher cell membrane potential were observed and thus demonstrated the changes in the cell membrane induced by multidrug resistance. Also, the ratios of GSH/GSSG, ATP/ADP and ATP/AMP were significantly higher in MCF-7/ADR cells relative to MCF-7/S cells.

CONCLUSIONS

Lower cell membrane fluidity and higher cell membrane potential caused by the changes in lipid compositions, enhanced anti-oxidative ability and energy generation were involved in the development of the MDR. The specific alterations identified in this study may provide more information for overcoming MDR.

Metabolomics: a challenge for detecting and monitoring inborn errors of metabolism

Timely newborn screening and genetic profiling are crucial in early recognition and treatment of inborn errors of metabolism (IEMs). A proposed nosology of IEMs has inserted 1,015 well-characterized IEMs causing alterations in specific metabolic pathways. With the increasing expansion of metabolomics in clinical biochemistry and laboratory medicine communities, several research groups have focused their interest on the analysis of metabolites and their interconnections in IEMs. Metabolomics has the potential to extend metabolic information, thus allowing to achieve an accurate diagnosis for the individual patient and to discover novel IEMs. Structural and functional information on 247 metabolites associated with 147 IEMs and 202 metabolic pathways involved in various IEMs have been reported in the human metabolome data base (HMDB). For each metabolic gene, a new computational approach can be developed for predicting a set of metabolites, whose concentration is predicted to change after gene knockout in urine, blood and other biological fluids. Both targeted and untargeted mass spectrometry (MS)-based metabolomic approaches have been used to expand the range of disease-associate metabolites. The quantitative targeted approach, in conjunction with chemometrics, can be considered a basic tool for validating known diagnostic biomarkers in various metabolic disorders. The untargeted approach broadens the identification of new biomarkers in known IEMs and allows pathways analysis. Urine is an ideal biological fluid for metabolomics in neonatology; however, the lack of standardization of preanalytical phase may generate potential interferences in metabolomic studies. The integration of genomic and metabolomic data represents the current challenge for improving diagnosis and prognostication of IEMs. The goals consist in identifying both metabolically active loci and genes relevant to a disease phenotype, which means deriving disease-specific biological insights.

Fully-automated systems and the need for global approaches should exhort clinical labs to reinvent routine MS analysis?

Today, many LC–high-resolution MS instruments have become affordable, easy-to-use, sensitive and quantitative. Meanwhile, there is an increased need for more comprehensive approaches. However, omics analyses are still restricted to specialists whereas, in hospitals, routine analyses are targeted and quantitative and represent the main and heavy tasks. But the availability of fully automated LC–MS instruments that can handle independently from sample extraction to result reporting, as well as the increasing biomedical interest for global approaches, clinical analytical workflow should be reorganized. Bioanalysts are now in the position to develop/implement clinical metabolomics or proteomics as routine analyses. In this article, this coming evolution and the reasons to implement global/omics determinations as routine analysis, is described.

LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study

Today’s high-resolution mass spectrometers (HRMS) allow bioanalysts to perform untargeted/global determinations that can reveal unexpected compounds or concentrations in a patient’s sample. This could be performed for preliminary diagnosis attempts when usual diagnostic processes and targeted determinations fail. We have evaluated an untargeted diagnostic screening (UDS) procedure. UDS is a metabolome analysis that compares one sample (e.g., a patient) with control samples (a healthy population). Using liquid chromatography (LC)-HRMS full-scan analysis of human serum extracts and unsupervised data treatment, we have compared individual samples that were spiked with one xenobiotic or a higher level of one endogenous compound with control samples. After the use of different filters that drastically reduced the number of metabolites detected, the spiked compound was eventually revealed in each test sample and ranked. The proposed UDS procedure appears feasible and reliable to reveal unexpected xenobiotics (toxicology) or higher concentrations of endogenous metabolites. HRMS-based untargeted approaches could be useful as preliminary diagnostic screening when canonical processes do not reveal disease etiology nor establish a clear diagnosis and could reduce misdiagnosis. On the other hand, the risk of overdiagnosis of this approach should be reduced with mandatory biomedical interpretation of the patient’s UDS results and with confirmatory targeted and quantitative determinations.

Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients

The implementation of whole-exome sequencing in clinical diagnostics has generated a need for functional evaluation of genetic variants. In the field of inborn errors of metabolism (IEM), a diverse spectrum of targeted biochemical assays is employed to analyze a limited amount of metabolites. We now present a single-platform, high-resolution liquid chromatography quadrupole time of flight (LC-QTOF) method that can be applied for holistic metabolic profiling in plasma of individual IEM-suspected patients. This method, which we termed "next-generation metabolic screening" (NGMS), can detect >10,000 features in each sample. In the NGMS workflow, features identified in patient and control samples are aligned using the "various forms of chromatography mass spectrometry (XCMS)" software package. Subsequently, all features are annotated using the Human Metabolome Database, and statistical testing is performed to identify significantly perturbed metabolite concentrations in a patient sample compared with controls. We propose three main modalities to analyze complex, untargeted metabolomics data. First, a targeted evaluation can be done based on identified genetic variants of uncertain significance in metabolic pathways. Second, we developed a panel of IEM-related metabolites to filter untargeted metabolomics data. Based on this IEM-panel approach, we provided the correct diagnosis for 42 of 46 IEMs. As a last modality, metabolomics data can be analyzed in an untargeted setting, which we term "open the metabolome" analysis. This approach identifies potential novel biomarkers in known IEMs and leads to identification of biomarkers for as yet unknown IEMs. We are convinced that NGMS is the way forward in laboratory diagnostics of IEMs.

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome

Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

Newborn Screening: History, Current Status, and Future Directions

Newborn screening programs aim to achieve presymptomatic diagnosis of treatable disorders allowing for early initiation of medical care to prevent or reduce significant morbidity and mortality. Many of the conditions included in the newborn screening panels are inborn errors of metabolism; however, screening for endocrine, hematologic, immunologic, and cardiovascular diseases, and hearing loss is also included in many panels. Newborn screening tests are not diagnostic and therefore diagnostic testing is needed to confirm or exclude the suspected diagnosis. Further advancement in technology is expected to allow continuous expansion of newborn screening.

Biofluid Metabolomics in Preterm Birth Research

This article presents an account of the research carried out so far in the use of metabolomics to find biomarkers of preterm birth (PTB) in fetal, maternal, and newborn biofluids. Metabolomic studies have employed mainly nuclear magnetic resonance spectroscopy or mass spectrometry-based methodologies to analyze, on one hand, prenatal biofluids (amniotic fluid, maternal urine/maternal blood, cervicovaginal fluid) to identify predictive biomarkers of PTB, and on the other hand, biofluids collected at or after birth (amniotic fluid, umbilical cord blood, newborn urine, and newborn blood, maternal blood, or breast milk) to assess and follow up the health status of PTB babies. Besides advancing on the biochemical knowledge of PTB metabolism mainly during the in utero period and at birth, the work carried out has also helped to identify important requirements related to experimental design and analytical protocol that need to be addressed, if translation of these biomarkers to the clinic is to be envisaged. An outlook of possible future developments for the translation of laboratory results to the clinic is presented.

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

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. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. 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. The latter revealed that prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but if VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months.

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

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.

Newborn screening: a review of history, recent advancements, and future perspectives in the era of next generation sequencing

PURPOSE OF REVIEW

The purpose of this review is to summarize the development and recent advancements of newborn screening.

RECENT FINDINGS

Early initiation of medical care has modified the outcome for many disorders that were previously associated with high morbidity (such as cystic fibrosis, primary immune deficiencies, and inborn errors of metabolism) or with significant neurodevelopmental disabilities (such as phenylketonuria and congenital hypothyroidism). The new era of mass spectrometry and next generation sequencing enables the expansion of the newborn screen panel, and will help to address technical issues such as turnaround time, and decreasing false-positive and false-negative rates for the testing.

SUMMARY

The newborn screening program is a successful public health initiative that facilitates early diagnosis of treatable disorders to reduce long-term morbidity and mortality.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era

Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of “omic” technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent “omic” technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era.

A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria

BACKGROUND

Different pathophysiological mechanisms have been described in phenylketonuria (PKU) but the indirect metabolic consequences of metabolic disorders caused by elevated Phe or low Tyr concentrations remain partially unknown. We used a multiplatform metabolomics approach to evaluate the metabolic signature associated with Phe and Tyr.

MATERIAL AND METHODS

We prospectively included 10 PKU adult patients and matched controls. We analysed the metabolome profile using GC-MS (urine), amino-acid analyzer (urine and plasma) and nuclear magnetic resonance spectroscopy (urine). We performed a multivariate analysis from the metabolome (after exclusion of Phe, Tyr and directly derived metabolites) to explain plasma Phe and Tyr concentrations, and the clinical status. Finally, we performed a univariate analysis of the most discriminant metabolites and we identified the associated metabolic pathways.

RESULTS

We obtained a metabolic pattern from 118 metabolites and we built excellent multivariate models to explain Phe, Tyr concentrations and PKU diagnosis. Common metabolites of these models were identified: Gln, Arg, succinate and alpha aminobutyric acid. Univariate analysis showed an inverse correlation between Arg, alpha aminobutyric acid and Phe and a positive correlation between Arg, succinate, Gln and Tyr (p < 0.0003). Thus, we highlighted the following pathways: Arg and Pro, Ala, Asp and Glu metabolism.

DISCUSSION

We obtain a specific metabolic signature related to Tyr and Phe concentrations. We confirmed the involvement of different pathophysiological mechanisms previously described in PKU such as protein synthesis, energetic metabolism and oxidative stress. The metabolomics approach is relevant to explore PKU pathogenesis.

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

Untargeted metabolomic analysis for the clinical screening of inborn errors of metabolism

Global metabolic profiling currently achievable by untargeted mass spectrometry-based metabolomic platforms has great potential to advance our understanding of human disease states, including potential utility in the detection of novel and known inborn errors of metabolism (IEMs). There are few studies of the technical reproducibility, data analysis methods, and overall diagnostic capabilities when this technology is applied to clinical specimens for the diagnosis of IEMs. We explored the clinical utility of a metabolomic workflow capable of routinely generating semi-quantitative z-score values for ~900 unique compounds, including ~500 named human analytes, in a single analysis of human plasma. We tested the technical reproducibility of this platform and applied it to the retrospective diagnosis of 190 individual plasma samples, 120 of which were collected from patients with a confirmed IEM. Our results demonstrate high intra-assay precision and linear detection for the majority compounds tested. Individual metabolomic profiles provided excellent sensitivity and specificity for the detection of a wide range of metabolic disorders and identified novel biomarkers for some diseases. With this platform, it is possible to use one test to screen for dozens of IEMs that might otherwise require ordering multiple unique biochemical tests. However, this test may yield false negative results for certain disorders that would be detected by a more well-established quantitative test and in its current state should be considered a supplementary test. Our findings describe a novel approach to metabolomic analysis of clinical specimens and demonstrate the clinical utility of this technology for prospective screening of IEMs.

Metabonomics and diagnostics

Metabonomic techniques have considerable potential in the field of clinical diagnostics, typifying the application of a translational research paradigm. Care must be taken at all stages to apply appropriate methodology with accurate patient selection and profiling, and rigorous data acquisition and handling, to ensure clinical validity.An ever-increasing number of publications in a wide range of diseases and diverse patient groups suggest a variety of potential clinical uses; prospective studies in large validation cohorts are required to bring metabonomics into routine clinical practice. In this chapter, the utility of metabonomics as a diagnostic tool will be discussed.

Liquid extraction surface analysis field asymmetric waveform ion mobility spectrometry mass spectrometry for the analysis of dried blood spots

LESA mass spectrometry coupled with high field asymmetric waveform ion mobility spectrometry (FAIMS) for the analysis of dried blood spots.