Advances in analytical mass spectrometry to improve screening for inherited metabolic diseases

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity

The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies.

Human metabolism is controlled through basic kinetic regulatory mechanisms, where the overall system aims to maintain a state of homeostasis. In response to external perturbations, such as environmental influences, nutrition or physical exercise, circulating metabolites show specific kinetic response patterns, which can be computationally modeled. In this work, we searched for dynamic metabolic biomarker candidates and analyzed specific kinetic mechanisms from longitudinal metabolic concentration data, obtained through a cycle ergometry stress test. In total, 110 metabolites measured from blood samples of 47 individuals were analyzed using tandem mass spectrometry (MS/MS). Dynamic biomarker candidates could be selected based on the amplitudes of changes in metabolite concentrations and the significance of statistical hypothesis testing. We were able to characterize specific kinetic patterns for groups of similarly behaving metabolites. Kinetic shape templates were identified, defining basic kinetic response patterns to physical exercise, such as sustained, early, late and other shape forms. The presented approach contributes to a better understanding of (patho)physiological biochemical mechanisms in human health, disease or during drug therapy, by offering tools for classifying dynamic biomarker candidates and for modeling and characterizing kinetic regulatory mechanisms from longitudinal experimental data.

Metabolic biomarkers for chronic kidney disease

Chronic kidney disease (CKD) is an increasingly recognized burden for patients and health care systems with high (and growing) global incidence and prevalence, significant mortality, and disproportionately high treatment costs. Yet, the available diagnostic tools are either impractical in clinical routine or have serious shortcomings impeding a well-informed disease management although optimized treatment strategies with proven benefits for the patients have become available. Advances in bioanalytical technologies have facilitated studies that identified genomic, proteomic, and metabolic biomarker candidates, and confirmed some of them in independent cohorts. This review summarizes the CKD-related markers discovered so far, and focuses on compounds and pathways, for which there is quantitative data, substantiating evidence from translational research, and a mechanistic understanding of the processes involved. Also, multiparametric marker panels have been suggested that showed promising diagnostic and prognostic performance in initial analyses although the data basis from prospective trials is very limited. Large-scale studies, however, are underway and will provide the information for validating a set of parameters and discarding others. Finally, the path from clinical research to a routine application is discussed, focusing on potential obstacles such as the use of mass spectrometry, and the feasibility of obtaining regulatory approval for targeted metabolomics assays.

Addressing the needs of traumatic brain injury with clinical proteomics

Background

Neurotrauma or injuries to the central nervous system (CNS) are a serious public health problem worldwide. Approximately 75% of all traumatic brain injuries (TBIs) are concussions or other mild TBI (mTBI) forms. Evaluation of concussion injury today is limited to an assessment of behavioral symptoms, often with delay and subject to motivation. Hence, there is an urgent need for an accurate chemical measure in biofluids to serve as a diagnostic tool for invisible brain wounds, to monitor severe patient trajectories, and to predict survival chances. Although a number of neurotrauma marker candidates have been reported, the broad spectrum of TBI limits the significance of small cohort studies. Specificity and sensitivity issues compound the development of a conclusive diagnostic assay, especially for concussion patients. Thus, the neurotrauma field currently has no diagnostic biofluid test in clinical use.

Content

We discuss the challenges of discovering new and validating identified neurotrauma marker candidates using proteomics-based strategies, including targeting, selection strategies and the application of mass spectrometry (MS) technologies and their potential impact to the neurotrauma field.

Summary

Many studies use TBI marker candidates based on literature reports, yet progress in genomics and proteomics have started to provide neurotrauma protein profiles. Choosing meaningful marker candidates from such ‘long lists’ is still pending, as only few can be taken through the process of preclinical verification and large scale translational validation. Quantitative mass spectrometry targeting specific molecules rather than random sampling of the whole proteome, e.g., multiple reaction monitoring (MRM), offers an efficient and effective means to multiplex the measurement of several candidates in patient samples, thereby omitting the need for antibodies prior to clinical assay design. Sample preparation challenges specific to TBI are addressed. A tailored selection strategy combined with a multiplex screening approach is helping to arrive at diagnostically suitable candidates for clinical assay development. A surrogate marker test will be instrumental for critical decisions of TBI patient care and protection of concussion victims from repeated exposures that could result in lasting neurological deficits.

Advancing the high throughput identification of liver fibrosis protein signatures using multiplexed ion mobility spectrometry

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography--ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization.

Screening criteria: the need to deal with new developments and ethical issues in newborn metabolic screening

Newborn metabolic screening is the most widespread application of screening technology and provides the most comprehensive application of genetics in health services, where the Guthrie blood spot cards allow screening for metabolic diseases in close to 100 % of all newborn babies. Despite over 40 years of use and significant benefits to well in excess of 100,000 children worldwide, there is remarkably little consensus in what conditions should be screened for and response to new advances in medicine relating to programme expansion. In this article, the international criteria for newborn metabolic screening are considered, and we propose that these criteria are poorly developed in relation to the baby, its family and society as a whole. Additionally, the ethical issues that should inform the application of screening criteria are often not developed to a level where a consensus might easily be achieved. We also consider that when family interests are factored in to the decision-making process, they have a significant influence in determining the list of diseases in the panel, with countries or states incorporating family and societal values being the most responsive. Based on our analysis, we propose that decision criteria for metabolic screening in the newborn period should be adapted to specifically include parent and family interests, community values, patients’ rights, duties of government and healthcare providers, and ethical arguments for action in the face of uncertainty.

Advances in hemoglobinopathy detection and identification

Hemoglobin disorders consist of two different groups, the structural hemoglobin variants and the thalassemias. The structural hemoglobin variants typically are based on the point mutations in the alpha- or beta-globin chain that results in a single-amino acid substitution in the corresponding globin chain, whereas thalassemias are caused by quantitative reduction in globin chain synthesis. Various techniques are applied for the laboratory investigation of these diseases, among them mass spectrometry (MS) for the detection and identification of structural hemoglobin variants and array techniques for the thalassemias. In this review, we present in the first part the most important mass spectrometric techniques applied in hemoglobin variant detection and identification and discuss several important aspects of this analysis technique in hematology. In the second part, the DNA analysis techniques used in hemoglobin analysis, such as reverse hybridization or microarray-based comparative genomic hybridization (CGH) techniques, are briefly discussed.

Selected reaction monitoring applied to proteomics

Selected reaction monitoring (SRM) performed on triple quadrupole mass spectrometers has been the reference quantitative technique to analyze small molecules for several decades. It is now emerging in proteomics as the ideal tool to complement shotgun qualitative studies; targeted SRM quantitative analysis offers high selectivity, sensitivity and a wide dynamic range. However, SRM applied to proteomics presents singularities that distinguish it from small molecules analysis. This review is an overview of SRM technology and describes the specificities and the technical aspects of proteomics experiments. Ongoing developments aiming at increasing multiplexing capabilities of SRM are discussed; they dramatically improve its throughput and extend its field of application to directed or supervised discovery experiments.

Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting

BACKGROUND

Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study.

METHODOLOGY/PRINCIPAL FINDINGS

40 individuals with self-reported diabetes and 60 controls (male, over 54 years) were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol), ketone bodies (3-hydroxybutyrate), and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid).

CONCLUSIONS/SIGNIFICANCE

Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate), lipid metabolism (glycerophospholipids, free fatty acids), and interaction with the gut microflora (bile acids). Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.

Sialic acid-focused quantitative mouse serum glycoproteomics by multiple reaction monitoring assay

Despite increasing importance of protein glycosylation, most of the large-scale glycoproteomics have been limited to profiling the sites of N-glycosylation. However, in-depth knowledge of protein glycosylation to uncover functions and their clinical applications requires quantitative glycoproteomics eliciting both peptide and glycan sequences concurrently. Here we describe a novel strategy for the multiplexed quantitative mouse serum glycoproteomics based on a specific chemical ligation, namely, reverse glycoblotting technique, focusing sialic acids and multiple reaction monitoring (MRM). LC-MS/MS analysis of de-glycosylated peptides identified 270 mouse serum peptides (95 glycoproteins) as sialylated glycopeptides, of which 67 glycopeptides were fully characterized by MS/MS analyses in a straightforward manner. We revealed the importance of a fragment ion containing innermost N-acetylglucosamine (GlcNAc) residue as MRM transitions regardless the sequence of the peptides. Versatility of the reverse glycoblotting-assisted MRM assays was demonstrated by quantitative comparison of 25 targeted glycopeptides from 16 proteins between mice with homo and hetero types of diabetes disease model.

Dissection of biochemical borderline phenotypes in carriers and genetic variants of medium-chain acyl-CoA dehyrogenase deficiency: implications for newborn screening [corrected]

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) represents a potentially fatal fatty acid beta-oxidation disorder. Newborn screening (NBS) by tandem mass spectrometry (MS/MS) has been implemented worldwide, but is associated with unresolved questions regarding population heterogeneity, burden on healthy carriers, cut-off policies, false-positive and negative rates. In a retrospective case-control study, 333 NBS samples showing borderline acylcarnitine patterns but not reaching recall criteria were genotyped for the two most common mutations (c.985A>G/c.199C>T) and compared with genotypes and acylcarnitines of 333 controls, 68 false-positives, and 34 patients. c.985A>G was more frequently identified in the study group and false-positives compared to controls (1:4.3/1:2.3 vs. 1:42), whereas c.199C>T was found more frequently only within the false-positives (1:23). Biochemical criteria were devised to differentiate homozygous (c.985A>G), compound heterozygous (c.985A>G/c.199C>T), and heterozygous individuals. Four false-negatives were identified because our initial algorithm required an elevation of octanoylcarnitine (C(8)) and three secondary markers in the initial and follow-up sample. The new approach allowed a reduction of false-positives (by defining high cut-offs: 1.4 micromol/l for C(8); 7 for C(8)/C(12)) and false-negatives (by sequencing the ACADM gene of few suspicious samples). Our validation strategy is able to differentiate healthy carriers from patients doubling the positive predictive value (42-->88%) and to target NBS to MCADD-subsets with potentially higher risk of adverse outcome. It remains controversial, if NBS programs should aim at identifying all subsets of all diseases included. Because the natural course of milder variants cannot be assessed by observational studies, our strategy could serve as a general model for evaluation of MS/MS-based NBS.

Determination of EDTA in dried blood samples by tandem mass spectrometry avoids serious errors in newborn screening

Newborn screening programs use whole blood dried on filter paper as the standard specimen. Metabolites are reasonably stable and can easily be sent to screening laboratories by regular mail. The recommended sample collection procedure is to spot native blood without anticoagulants onto the filter paper, because anticoagulants can interfere with the different laboratory methods. However, visual examination of the blood spots cannot always detect contamination. In this study, whole blood was drawn by venous puncture from a healthy volunteer, spiked with the corresponding metabolites and EDTA, and spotted onto filter paper. TSH and 17alpha-hydroxyprogesterone were determined by time resolved fluoroimmunoassays with the AutoDelfia system. Total galactose, biotinidase activity, and galactose-1-phosphate uridyltransferase activity were measured photometrically or fluorometrically. Succinyl acetone was estimated indirectly through the inhibition of porphobilinogen synthase activity (PBGS assay). EDTA, amino acids, and acylcarnitines were converted to the corresponding butyl esters, after extraction with methanol, and analysed by LC-MS/MS. EDTA contamination gives falsely elevated 17-OHP values and falsely reduced TSH and PBGS values. The inclusion of an EDTA determination in routine screening revealed that at least 0.06% of newborn screening samples were contaminated with EDTA. In conclusion, non-conformity during the pre-analytical phase is a source of false positive and false negative screening results. Determination of EDTA from NBS blood spots can reliably identify these samples and prevent screening errors.

Development and Evaluation of Quality Control Dried Blood Spot Materials in Newborn Screening for Lysosomal Storage Disorders

Background: Lysosomal storage disorders (LSDs) comprise more than 40 genetic diseases that result in the accumulation of products that would normally be degraded by lysosomal enzymes. A tandem mass spectrometry (MS/MS)-based method is available for newborn screening for 5 LSDs, and many laboratories are initiating pilot studies to evaluate the incorporation of this method into their screening panels. We developed and evaluated dried blood spot (DBS) QC materials for LSDs and used the MS/MS method to investigate their suitability for LSD QC monitoring.

Methods: We incubated 3.2-mm punches from DBS controls for 20–24 h with assay cocktails containing substrate and internal standard. Using MS/MS, we quantified the resulting product and internal standard. Samples were run in triplicate for 3 consecutive days, and results were reported as product-to-internal standard ratios and enzyme activity units (μmol/L/h).

Results: Enzyme activity interday imprecision (CV) for the high, medium, and low series were 3.4%–14.3% for galactocerebroside α-galactosidase, 6.8%–24.6% for acid α-galactosidase A, 7.36%–22.1% for acid sphingomyelinase, 6.2%–26.2% for acid α-glucocerebrosidase, and 7.0%–24.8% for lysosomal acid α-glucosidase (n = 9). In addition, DBS stored at −20° and 4 °C showed minimal enzyme activity loss over a 187-d period. DBS stored at 37° and 45 °C had lower activity values over the 187-day evaluation time.

Conclusions: Suitable QC materials for newborn screening of LSDs were developed for laboratories performing DBS LSD screening. Good material linearity was observed, with goodness-of-fit values of 0.953 and higher. The QC materials may be used by screening laboratories that perform LSD analysis by MS and/or more conventional fluorescence-based screening methods.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

A mass spectrometric strategy for profiling glycoproteinoses, Pompe disease, and sialic acid storage diseases

Glycoproteinoses, Pompe disease, and sialic acid storage diseases are characterized by a massive accumulation of unprocessed oligosaccharides and/or glycoconjugates in urine. The identification of these glycocompounds is essential for a proper diagnosis. In this study, we investigated the potential of MALDI-TOF-MS to identify glycocompounds present in urine from patients with different inborn errors of glycan metabolism. Urinary glycocompounds were permethylated, and analyzed using GC-MS and MALDI-TOF-MS. In order to confirm tentative assignments, a second aliquot of urine was purified on a C18 Sep-Pak cartridge and glycocompounds were desalted on a column of nonporous graphitized carbon. The glycocompounds were then sequentially on-plate digested using an array of exoglycosidases. A range of disease-specific oligosaccharides as well as glycopeptides was identified for all oligosacchariduria models. In addition, free sialic acid accumulated in urine from a patient suffering from French-type sialuria, has been detected by a GC-MS approach, which could be applied to other sialic acid storage diseases. This procedure is simple, and can be performed in few simple steps in less than 24 h. This current method can be applied for newborn screening for other inherited metabolic diseases as well as for assessing treatments in clinical trials.

Quantification of urinary zwitterionic organic acids using weak-anion exchange chromatography with tandem MS detection

A rapid and accurate quantitative method was developed and validated for the analysis of four urinary organic acids with nitrogen containing functional groups, formiminoglutamic acid (FIGLU), pyroglutamic acid (PYRGLU), 5-hydroxyindoleacetic acid (5-HIAA), and 2-methylhippuric acid (2-METHIP) by liquid chromatography tandem mass spectrometry (LC/MS/MS). The chromatography was developed using a weak anion-exchange amino column that provided mixed-mode retention of the analytes. The elution gradient relied on changes in mobile phase pH over a concave gradient, without the use of counter-ions or concentrated salt buffers. A simple sample preparation was used, only requiring the dilution of urine prior to instrumental analysis. The method was validated based on linearity (r2>or=0.995), accuracy (85-115%), precision (C.V.<12%), sample preparation stability (<or=5%, 72 h), and established patient ranges. The method was found to be both efficient and accurate for the analysis of urinary zwitterionic organic acids.

Inborn errors of isoleucine degradation: a review

Three inborn errors have been identified in the pathway of isoleucine degradation. Deficiency of beta-ketothiolase (beta-KT, also known as T2, mitochondrial acetoacetyl-CoA thiolase and acetyl-CoA acetyltransferase 1) is a well-described disorder which presents with acute episodic ketoacidosis. In contrast, short/branched-chain acyl-CoA dehydrogenase (SBCAD) and 2-methyl-3-hydroxybutyryl-CoA dehydrogenase (MHBD) deficiencies are recently described and relatively rare defects which present with predominantly neurological manifestations, although acute metabolic decompensation may occur in the early newborn period. Careful examination of urine organic acids is required for identification and differential diagnosis of these disorders, with awareness that the abnormalities may be subtle and variable. Tandem MS analysis of acylcarnitines may reveal elevated C5 (SBCAD) or C5:1 and/or OH-C5 species (MHBD and beta-KT deficiencies) but the abnormalities are non-diagnostic and may be intermittent or absent. Confirmation of diagnosis is therefore advisable by specific enzyme assay and/or mutation analysis of the ACAT1 (beta-KT), ACADSB (SBCAD) or HADH2 (MHBD) genes. The latter is located on the X chromosome, accounting for the milder clinical phenotype in females. If beta-KT deficiency is diagnosed early and treated by fasting avoidance and modest protein restriction, ketoacidosis episodes can be prevented and the prognosis is excellent. The role of treatment in SBCAD deficiency remains unclear pending further delineation of its clinical phenotype and pathogenicity, particularly regarding asymptomatic individuals detected by expanded newborn screening. The ineffectiveness of isoleucine restriction in MHBD deficiency is consistent with the additional roles of this multifunctional enzyme in sex steroid and neurosteroid metabolism and its interaction with amyloid-beta peptide.

Protein biomarker discovery and validation: the long and uncertain path to clinical utility

Better biomarkers are urgently needed to improve diagnosis, guide molecularly targeted therapy and monitor activity and therapeutic response across a wide spectrum of disease. Proteomics methods based on mass spectrometry hold special promise for the discovery of novel biomarkers that might form the foundation for new clinical blood tests, but to date their contribution to the diagnostic armamentarium has been disappointing. This is due in part to the lack of a coherent pipeline connecting marker discovery with well-established methods for validation. Advances in methods and technology now enable construction of a comprehensive biomarker pipeline from six essential process components: candidate discovery, qualification, verification, research assay optimization, biomarker validation and commercialization. Better understanding of the overall process of biomarker discovery and validation and of the challenges and strategies inherent in each phase should improve experimental study design, in turn increasing the efficiency of biomarker development and facilitating the delivery and deployment of novel clinical tests.

Metabolic profiling technologies for biomarker discovery in biomedicine and drug development

The state-of-the-art of nuclear magnetic resonance spectroscopy, mass spectrometry and statistical tools for the acquisition and evaluation of complex multidimensional spectroscopic data in metabolic profiling is reviewed in this article. The continuous evolution of the sensitivity, precision and throughput has made these technologies powerful and extremely robust tools for application in systems biology, pharmaceutical and diagnostics research. Particular emphasis is also given to the collection and storage of biological samples that are subjected to metabolite profiling. Selected examples from preclinical and clinical applications are paradigmatically shown. These illustrate the power of the profiling technologies for characterizing the metabolic phenotype of healthy, diseased and treated subjects. The complexity of disease and drug treatment is asking for an adequate response by integrated and comprehensive metabolite profiling approaches that allow the discovery of new combinations of metabolic biomarkers.

Clinical genetic evaluation of the child with mental retardation or developmental delays

This clinical report describes the clinical genetic evaluation of the child with developmental delays or mental retardation. The purpose of this report is to describe the optimal clinical genetics diagnostic evaluation to assist pediatricians in providing a medical home for children with developmental delays or mental retardation and their families. The literature supports the benefit of expert clinical judgment by a consulting clinical geneticist in the diagnostic evaluation. However, it is recognized that local factors may preclude this particular option. No single approach to the diagnostic process is supported by the literature. This report addresses the diagnostic importance of clinical history, 3-generation family history, dysmorphologic examination, neurologic examination, chromosome analysis (> or =650 bands), fragile X molecular genetic testing, fluorescence in situ hybridization studies for subtelomere chromosome rearrangements, molecular genetic testing for typical and atypical presentations of known syndromes, computed tomography and/or magnetic resonance brain imaging, and targeted studies for metabolic disorders.

Expanded newborn screening of inherited metabolic disorders by tandem mass spectrometry: Clinical and laboratory aspects

Newborn screening started in the 1960s for the purpose of identifying phenylketonuric patients to begin early intervention and to prevent mental retardation in these patients. Soon thereafter, screening programs expanded to include additional genetic disorders added individually one at a time. In the 1980s, tandem mass spectrometry (MS/MS) was introduced in clinical laboratories, and in the 1990s, the technique was used for newborn screening. Unlike measuring one analyte at a time, MS/MS allows measurement of >40 analytes, in a few minutes with the use of a single assay. Currently, MS/MS is being used for the identification of several amino acid, organic acid and fatty acid disorders. Several states in the United States and many other countries are using MS/MS in newborn screening. However, there is a significant disparity among different newborn screening programs for disorders being screened by MS/MS and many other challenges are faced by the expanded newborn screening. It is anticipated that in the future the use of MS/MS in newborn screening will expand both at the analyte and geographic levels. Clinicians and laboratory scientists should become familiar with MS/MS, disorders being screened in their patients' population and the future of this emerging technology.

Nutrition and food science go genomic

The wealth of genomic information and high-throughput profiling technologies are now being exploited by scientists in the disciplines of nutrition and food science. Diet and food components are prime environmental factors that affect the genome, transcriptome, proteome and metabolome, and this life-long interaction defines the health or disease state of an individual. For the first time the interaction of foods, and individual food constituents, with the biological systems can be defined on a molecular basis. Profiling technologies are used in basic-science applications for identifying the mode of action of foods or particular ingredients, and are similarly taken into the science-driven development of foods with a defined biofunctionality. Biomarker profiles and patterns derived from genomics applications in humans should guide nutrition and food science in developing evidence-based dietary recommendations and health-promoting foods.

Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins

Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2-22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2-7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R(2)) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 microg/ml) indicates that proteins down to the microg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)).

Biomarker Discovery, Disease Classification, and Similarity Query Processing on High-Throughput MS/MS Data of Inborn Errors of Metabolism

In newborn errors of metabolism, biomarkers are urgently needed for disease screening, diagnosis, and monitoring of therapeutic interventions. This article describes a 2-step approach to discovermetabolic markers, which involves (1) the identification ofmarker candidates and (2) the prioritization of thembased on expert knowledge of diseasemetabolism. For step 1, the authors developed a new algorithm, the biomarker identifier (BMI), to identifymarkers fromquantified diseased versus normal tandemmass spectrometry data sets. BMI produces a ranked list ofmarker candidates and discards irrelevant metabolites based on a quality measure, taking into account the discriminatory performance, discriminatory space, and variance ofmetabolites’ concentrations at the state of disease. To determine the ability of identified markers to classify subjects, the authors compared the discriminatory performance of several machine-learning paradigms and described a retrieval technique that searches and classifies abnormal metabolic profiles from a screening database. Seven inborn errors of metabolism— phenylketonuria (PKU), glutaric acidemia type I (GA-I), 3-methylcrotonylglycinemia deficiency (3-MCCD), methylmalonic acidemia (MMA), propionic acidemia (PA), medium-chain acylCoAdehydrogenase deficiency (MCADD), and 3-OH longchain acyl CoA dehydrogenase deficiency (LCHADD)—were investigated. All primarily prioritized marker candidates could be confirmed by literature. Somenovel secondary candidateswere identified (i.e., C16:1 andC4DCfor PKU, C4DCfor GA-I, and C18:1 forMCADD), which require further validation to confirmtheir biochemical role during health and disease.