Daily Variation of Serum Acylcarnitines and Amino Acids

Large-Scale Population-Based Studies of Blood Metabolome and Brain Health

Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n > 50 metabolites) and brain health reported in large-scale studies (n > 500 individuals).

Utilizing metabolomics to identify potential biomarkers and perturbed metabolic pathways in osteoarthritis: A systematic review

PURPOSE

Osteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and characteristic radiographic findings, such as joint space narrowing. Currently, there are no laboratory findings that are specific to a diagnosis of OA. The purpose of this systematic review is to evaluate the state of current studies of metabolomic biomarkers that can aid in the diagnosis and treatment of OA.

METHODS

Articles were gathered from PubMed and Web of Science using the search terms "osteoarthritis" and "biomarkers" and "metabolomics". Last search of databases took place December 3rd, 2022. Duplicates were manually screened, along with any other results that were not original journal articles. Only original reports involving populations with diagnosed primary or secondary OA (human participants) or surgically induced OA (animal participants) and a healthy control group for comparison were considered for inclusion. Metabolites and metabolic pathways reported in included articles were then manually extracted and evaluated for importance based on reported a priori p-values and/or area under the receiver-operator curve (AUC).

RESULTS

Of the 161 results that were returned in the database searches, 43 unique articles met the inclusion criteria. Articles were categorized based on body fluid analyzed: 6 studies on urine samples, 13 studies on plasma samples, 11 studies on synovial fluid (SF) samples, 11 studies on serum samples, 1 study on both synovial fluid and serum, and 1 study that involved both plasma and synovial fluid. To synthesize results, individual metabolites, as well as metabolic pathways that involve frequently reported metabolites, are presented for each study. Indications as to whether metabolite levels were increased or decreased are also included if this data was included in the original articles.

CONCLUSIONS

These studies clearly show that there are a wide range of metabolic pathways perturbed in OA. For this period, there was no consensus on a single metabolite, or panel of metabolites, that would be clinically useful in early diagnosis of OA or distinguishing OA from a healthy control. However, many common metabolic pathways were identified in the studies, including TCA cycle, fatty acid metabolism, amino acid metabolism (notably BCAA metabolism and tryptophan metabolism via kynurenine pathway), nucleotide metabolism, urea cycle, cartilage matrix components, and phospholipid metabolism. Future research is needed to define effective clinical biomarkers of osteoarthritis from metabolomic and other data.

Metabolomic Profiling in Patients with Different Hemodynamic Subtypes of Severe Aortic Valve Stenosis

Severe aortic stenosis (AS) is a common pathological condition in an ageing population imposing significant morbidity and mortality. Based on distinct hemodynamic features, i.e., ejection fraction (EF), transvalvular gradient and stroke volume, four different AS subtypes can be distinguished: (i) normal EF and high gradient, (ii) reduced EF and high gradient, (iii) reduced EF and low gradient, and (iv) normal EF and low gradient. These subtypes differ with respect to pathophysiological mechanisms, cardiac remodeling, and prognosis. However, little is known about metabolic changes in these different hemodynamic conditions of AS. Thus, we carried out metabolomic analyses in serum samples of 40 AS patients (n = 10 per subtype) and 10 healthy blood donors (controls) using ultrahigh-performance liquid chromatography-tandem mass spectroscopy. A total of 1293 biochemicals could be identified. Principal component analysis revealed different metabolic profiles in all of the subgroups of AS (All-AS) vs. controls. Out of the determined biochemicals, 48% (n = 620) were altered in All-AS vs. controls (p < 0.05). In this regard, levels of various acylcarnitines (e.g., myristoylcarnitine, fold-change 1.85, p < 0.05), ketone bodies (e.g., 3-hydroxybutyrate, fold-change 11.14, p < 0.05) as well as sugar metabolites (e.g., glucose, fold-change 1.22, p < 0.05) were predominantly increased, whereas amino acids (e.g., leucine, fold-change 0.8, p < 0.05) were mainly reduced in All-AS. Interestingly, these changes appeared to be consistent amongst all AS subtypes. Distinct differences between AS subtypes were found for metabolites belonging to hemoglobin metabolism, diacylglycerols, and dihydrosphingomyelins. These findings indicate that relevant changes in substrate utilization appear to be consistent for different hemodynamic subtypes of AS and may therefore reflect common mechanisms during AS-induced heart failure. Additionally, distinct metabolites could be identified to significantly differ between certain AS subtypes. Future studies need to define their pathophysiological implications.

Short-term amino acid, clinicopathologic, and echocardiographic findings in healthy dogs fed a commercial plant-based diet

Consumer demand for commercially prepared plant-based (PB) dog food is increasing, but studies evaluating the short- or long-term effects of PB diets on canine health are lacking. The objective of this study was to assess the short-term amino acid (AA), clinicopathologic, and echocardiographic findings in 34 client-owned dogs fed a commercial extruded plant-based diet (PBD) in which pea protein was the primary protein source and 4 control dogs fed a commercial extruded traditional diet (TD). Plasma AA and whole blood taurine concentrations were measured in dogs at baseline and after 4 weeks on the PBD or the TD. Hematologic, serum biochemical, and echocardiographic testing were performed at baseline and after 12 weeks on the PBD or the TD. Four dogs in the PBD group did not complete the study. All essential AAs, except methionine, were higher in dogs after 4 weeks on the PBD compared to baseline. Taurine (plasma and whole blood) was also higher after 4 weeks on the PBD compared to baseline. A meaningful difference was detected in whole blood taurine between the PBD group and the control group at 4 weeks (P = .026) with the PBD group being higher. Median hematologic and biochemical results for the PBD group were within normal limits at baseline and at 12 weeks. In the PBD group, left ventricular internal diastolic dimension (LVIDd, P = < .001) and normalized LVIDd (P = .031) were higher 12 weeks post-PBD compared to baseline. There were no meaningful differences in left ventricular internal systolic dimension (LVIDs), normalized LVIDs, or fractional shortening 12 weeks post-PBD. There was no statistical evidence of difference between the 2 groups of dogs for any of the echocardiographic parameters at baseline or at 12 weeks. Essential AA or taurine deficiency was not observed in this cohort of dogs fed a commercial extruded PBD. Additionally, clinically relevant hematologic, serum biochemical and echocardiographic alterations were not detected. Further research is required to determine if long-term static feeding of PB diets can meet and maintain AA and other nutrient targets in dogs.

Metabolic features of adiposity and glucose homoeostasis among school-aged inuit children from Nunavik (Northern Quebec, Canada)

In contrast to most Indigenous people in Canada, Inuit appeared until recently to have been protected from type 2 diabetes (T2D) related to obesity. We assessed the associations of metabolites (amino acids, acylcarnitines) with adiposity and biomarkers of T2D in school-aged Inuit children of Nunavik (Canada). Concentrations of metabolite were measured in plasma samples from a cross-sectional analysis of 248 children (mean age = 10.8 years). We assessed associations of plasma metabolites with adiposity measures (BMI, skinfold thicknesses) and T2D markers (insulin, glucose, adiponectin). Plasma concentrations of valine and tyrosine were higher in obese and overweight children compared to those of normal weight children (P < 0.05). An increment of 1-SD in BMI (SD = 3.3 kg/m²) was statistically associated with an increment of 0.21 (95% CI: 0.08, 0.33) for valine, 0.15 (95% CI: 0.02, 0.27) for isoleucine and 0.17 (95% CI: 0.04, 0.29) for tyrosine. Insulin concentration increased with concentrations of all amino acids (P < 0.05) except methionine. None of the acylcarnitines measured were statistically significantly associated with adiposity or T2D biomarkers A signature of metabolites, particularly higher levels of branched-chain amino acids, might allow for early detection of T2D among school-aged Inuit children.

High-Throughput Fractionation Coupled to Mass Spectrometry for Improved Quantitation in Metabolomics

Metabolomics is emerging as an important field in life sciences. However, a weakness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis and the occurrence of severe matrix effects in complex mixtures. To overcome this problem, we have developed an automated and fast fractionation module coupled online to MS. The fractionation is realized by the implementation of three consecutive high performance solid-phase extraction columns consisting of a reversed phase, mixed-mode anion exchange, and mixed-mode cation exchange sorbent chemistry. The different chemistries resulted in an efficient interaction with a wide range of metabolites based on polarity, charge, and allocation of important matrix interferences like salts and phospholipids. The use of short columns and direct solvent switches allowed for fast screening (3 min per polarity). In total, 50 commonly reported diagnostic or explorative biomarkers were validated with a limit of quantification that was comparable with conventional LC–MS(/MS). In comparison with a flow injection analysis without fractionation, ion suppression decreased from 89% to 25%, and the sensitivity was 21 times higher. The validated method was used to investigate the effects of circadian rhythm and food intake on several metabolite classes. The significant diurnal changes that were observed stress the importance of standardized sampling times and fasting states when metabolite biomarkers are used. Our method demonstrates a fast approach for global profiling of the metabolome. This brings metabolomics one step closer to implementation into the clinic.

Sexual Dimorphism in Energy Metabolism of Wistar Rats Using Data Analysis

The prevalence of some chronic diseases, such as cancer or neurodegenerative disorders, differs between sexes. Animal models provide an important tool to adopt potential therapies from preclinical studies to humans. Laboratory rats are the most popular animals in toxicology, neurobehavioral, or cancer research. Our study aimed to reveal the basic differences in blood metabolome (amino acids, biogenic amines, and acylcarnitines) of the adult male (n = 10) and female (n = 10) Wistar rats. Partial least square-discrimination analysis (PLS-DA) and a variance im portance in projection (VIP) score was used to identify the key sex-specific metabolites. All groups of metabolites, as the main markers of energy metabolism, showed a significant sex-dependent pattern. The most important features calculated in PLS-DA according to VIP score were free carnitine (C0), tyrosine (Tyr), and acylcarnitine C5-OH. While aromatic amino acids, such as Tyr and phenylalanine (Phe), were significantly elevated in the blood plasma of males, tryptophan (Trp) was found in higher levels in the blood plasma of females. Besides, significant sex-related changes in urea cycle were found. Our study provides an important insight into sex-specific differences in energy metabolism in rats and indicates that further studies should consider sex as the main aspect in design and data interpretation.

Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review

Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.

Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies

Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings.

Metabolomics Reveals that the Type of Protein in a High-Fat Meal Modulates Postprandial Mitochondrial Overload and Incomplete Substrate Oxidation in Healthy Overweight Men

Background

A meal rich in saturated fatty acids induces a postprandial metabolic challenge. The type of dietary protein may modulate postprandial metabolism.

Objective

We studied the effect of dietary protein type on postprandial changes in the metabolome after a high-fat meal.

Methods

In a 3-period, crossover, postprandial study, 10 healthy overweight men with an elevated waist circumference (>94 cm) ingested high-fat meals made up of cream fat (70% of energy), sucrose (15% energy), and protein (15% energy) from either casein (CAS), whey protein (WHE), or α-lactalbumin-enriched whey protein (LAC). Urine collected immediately before and 2, 4, and 6 h after the meal was analyzed for metabolomics, a secondary outcome of the clinical study. We used mixed-effect models, partial least-square regression, and pathway enrichment analysis.

Results

At 4 and 6 h after the meal, the postprandial metabolome was found to be fully discriminated according to protein type. We identified 17 metabolites that significantly explained the effect of protein type on postprandial metabolomic changes (protein-time interaction). Among this signature, acylcarnitines and other acylated metabolites related to fatty acid or amino acid oxidation were the main discriminant features. The difference in metabolic profiles was mainly explained by urinary acylcarnitines and some other acylated products (protein type, Ps < 0.0001), with a dramatically greater increase (100- to 1000-fold) after WHE, and to a lesser extent after LAC, as compared with CAS. Pathway enrichment analysis confirmed that the type of protein had modified fatty acid oxidation (P < 0.05).

Conclusion

Taken together, our results indicate that, in healthy overweight men, the type of protein in a high-fat meal interplays with fatty acid oxidation with a differential accumulation of incomplete oxidation products. A high-fat meal containing WHE, but not CAS, resulted in this outpacing of the tricarboxylic acid cycle. This study was registered at clinicaltrials.gov as NCT00931151.

The C3dg Fragment of Complement Is Superior to Conventional C3 as a Diagnostic Biomarker in Systemic Lupus Erythematosus

Introduction/objectives

In 2012, hypocomplementemia was included in the classification criteria of systemic lupus erythematosus (SLE). The suggested measurement of C3 or C4 often reflect disease activity poorly. Our objective was to establish an assay measuring C3dg, which is generated following complement activation, and to evaluate the assay in a cross-sectional SLE cohort.

Method

We included SLE patients (n = 169) and controls (n = 170) and developed a modified C3dg assay where C3dg fragments were separated from the large plasma proteins by polyethylene glycol (PEG), and the supernatant containing the C3dg fragment was used for analysis in an antibody-based sandwich-type assay. Gel permeation chromatography and western blotting were used to establish the optimal conditions for PEG precipitation.

Results

16% PEG was optimal for separating C3dg from C3 and the larger protein fragments. The assay showed a high degree of stability when using EDTA plasma, and measurements correlated well with commercially available complement activation assays. SLE patients had higher concentrations in plasma of C3dg than controls (p < 0.05). ROC analysis showed that the C3dg activation fragment of C3 with an AUC of 0.96 (CI 0.94–0.98) was superior to C3 (AUC 0.52) in differentiating between patients and controls.

Conclusion

Our results present a modified assay for the measurement of C3dg. We demonstrate that C3dg was superior to conventional C3 measurements in discriminating SLE patients from controls. We suggest that C3dg should be considered as a complement activation measurement in the SLE classification criteria.

Targeting human urinary metabolome by LC-MS/MS: a review

Urine is a biological matrix that contains hundreds of metabolic end products which constitute the urinary metabolome. The development and advances on LC-MS/MS have revolutionized the analytical study of biomolecules by enabling their accurate identification and quantification in an unprecedented manner. Nowadays, LC-MS/MS is helping to unveil the complexity of urine metabolome, and the results obtained have multiple biomedical applications. This review focuses on the targeted LC-MS/MS analysis of the urine metabolome. In the first part, we describe general considerations (from sample collection to quantitation) required for a proper targeted metabolic analysis. In the second part, we address the urinary analysis and recent applications of four relevant families: amino acids, catecholamines, lipids and steroids.

Metabolic Dysfunction in Heart Failure: Diagnostic, Prognostic, and Pathophysiologic Insights From Metabolomic Profiling

Metabolic impairment is an intrinsic component of heart failure (HF) pathophysiology. Although initially conceived as a myocardial defect, metabolic dysfunction is now recognized as a systemic process with complex interplay between the myocardium and peripheral tissues and organs. Specifically, HF-associated metabolic dysfunction includes alterations in substrate utilization, insulin resistance, defects in energy production, and imbalanced anabolic-catabolic signaling leading to cachexia. Each of these metabolic abnormalities is associated with significant morbidity and mortality in patients with HF; however, their detection and therapeutic management remains challenging. Given the difficulty in obtaining human cardiac tissue for research purposes, peripheral blood metabolomic profiling, a well-established approach for characterizing small-molecule metabolite intermediates from canonical biochemical pathways, may be a useful technology for dissecting biomarkers and mechanisms of metabolic impairment in HF. In this review, metabolic abnormalities in HF will be discussed with particular emphasis on the application of metabolomic profiling to detecting, risk stratifying, and identifying novel targets for metabolic therapy in this heterogeneous population.

Decreased long-chain acylcarnitines from insufficient β-oxidation as potential early diagnostic markers for Parkinson's disease

Increasing evidence shows that metabolic abnormalities in body fluids are distinguishing features of the pathophysiology of Parkinson’s disease. However, a non-invasive approach has not been established in the earliest or pre-symptomatic phases. Here, we report comprehensive double-cohort analyses of the metabolome using capillary electrophoresis/liquid chromatography mass-spectrometry. The plasma analyses identified 18 Parkinson’s disease-specific metabolites and revealed decreased levels of seven long-chain acylcarnitines in two Parkinson’s disease cohorts (n = 109, 145) compared with controls (n = 32, 45), respectively. Furthermore, statistically significant decreases in five long-chain acylcarnitines were detected in Hoehn and Yahr stage I. Likewise, decreased levels of acylcarnitine(16:0), a decreased ratio of acylcarnitine(16:0) to fatty acid(16:0), and an increased index of carnitine palmitoyltransferase 1 were identified in Hoehn and Yahr stage I of both cohorts, suggesting of initial β-oxidation suppression. Receiver operating characteristic curves produced using 12–14 long-chain acylcarnitines provided a large area of under the curve, high specificity and moderate sensitivity for diagnosing Parkinson’s disease. Our data demonstrate that a primary decrement of mitochondrial β-oxidation and that 12–14 long-chain acylcarnitines decreases would be promising diagnostic biomarkers for Parkinson’s disease.

Metabolic Response of Visceral White Adipose Tissue of Obese Mice Exposed for 5 Days to Human Room Temperature Compared to Mouse Thermoneutrality

Housing of laboratory mice at room temperature (22°C) might be considered a constant cold stress, which induces a thermogenic program in brown adipose tissue (BAT). However, the early adaptive response of white adipose tissue (WAT), the fat storage organ of the body, to a change from thermoneutrality to room temperature is not known. This was investigated here for various WAT depots, focusing on epididymal WAT (eWAT), widely used as reference depot. Male adult diet-induced obese (DIO) C57BL/6JOlaHsd mice housed at thermoneutrality (29°C), were for 5 days either switched to room temperature (22°C) or remained at thermoneutrality. Energy metabolism was continuously measured using indirect calorimetry. At the end of the study, serum metabolomics and WAT transcriptomics were performed. We confirmed activation of the thermogenic program in 22°C housed mice. Body weight and total fat mass were reduced. Whole body energy expenditure (EE) was increased, with a higher fatty acid to carbohydrate oxidation ratio and increased serum acylcarnitine levels, while energy intake was not significantly different between the two groups. Transcriptome analysis of eWAT identified tissue remodeling and inflammation as the most affected processes. Expression of pro-inflammatory M1 macrophage-related genes, and M1 over M2 macrophage ratio were decreased, which might be linked to an increased insulin sensitivity. Markers of thermogenesis were not altered in eWAT. Decreased expression of tryptophan hydroxylase 2 (Tph2) and cholecystokinin (Cck) might represent altered neuroendocrine signaling. eWAT itself does not show increased fatty acid oxidation. The three measured WATs, epididymal, mesenteric, and retroperitoneal, showed mainly similar responses; reduced inflammation (s100a8), decreased carbohydrate oxidation, and no or small differences in fatty acid oxidation. However, Ucp1 was only expressed and increased in rWAT in 22°C housed mice. Cck expression was decreased in the three WATs, significantly in eWAT and rWAT, in contrast to Tph2, which was decreased in eWAT while not expressed in mWAT and rWAT. Our data show that tissue remodeling, inflammation and neuroendocrine signaling are early responses in WAT to a moderate decrease in environmental temperature.

Longitudinal plasma metabolic profiles, infant feeding, and islet autoimmunity in the MIDIA study

AIMS

The aim of this study was to investigate the longitudinal plasma metabolic profiles in healthy infants and the potential association with breastfeeding duration and islet autoantibodies predictive of type 1 diabetes.

METHOD

Up to four longitudinal plasma samples from age 3 months from case children who developed islet autoimmunity (n = 29) and autoantibody-negative control children (n = 29) with the HLA DR4-DQ8/DR3-DQ2 genotype were analyzed using two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer for detection of small polar metabolites.

RESULTS

Plasma metabolite levels were found to depend strongly on age, with fold changes varying up to 50% from age 3 to 24 months (p < 0.001 after correction for multiple testing). Tyrosine levels tended to be lower in case children, but this was not significant after correction for multiple testing. Ornithine levels were lower in case children compared with the controls at the time of seroconversion, but the difference was not statistically significant after correcting for multiple testing. Breastfeeding for at least 3 months as compared with shorter duration was associated with higher plasma levels of isoleucine, and lower levels of methionine and 3,4-dihydroxybutyric acid at 3 months of age.

CONCLUSIONS

Plasma levels of several small, polar metabolites changed with age during early childhood, independent of later islet autoimmunity status and sex. Breastfeeding was associated with higher levels of branched-chain amino acids, and lower levels of methionine and 3,4-dihydroxybutyric acid.

Serum lipid alterations identified in chronic hepatitis B, hepatitis B virus-associated cirrhosis and carcinoma patients

The incidences of chronic hepatitis B (CHB), Hepatitis B virus (HBV)-associated cirrhosis and HBV-associated carcinoma are high and increasing. This study was designed to evaluate serum lipid metabolite changes that are associated with the progression from CHB to HBV-associated cirrhosis and ultimately to HBV-associated HCC. A targeted metabolomic assay was performed in fasting sera from 136 CHB patients, 104 HBV-associated cirrhosis, and 95 HBV-associated HCC using ultra-performance liquid chromatography triple quadrupole mass spectrometry. A total of 140 metabolites were identified. Clear separations between each two groups were obtained using the partial least squares discriminate analysis of 9 lipid metabolites. Progressively lower levels of long-chain lysophosphatidylcholines (lysoPC a C18:2, lysoPC a C20:3, lysoPC a C20:4) were observed from CHB to cirrhosis to carcinoma; lower levels of lysoPC a C20:4 were found in patients with higher model for end-stage liver disease in the same disease group; and lysoPC a C20:3 levels were lower in Child-Pugh Class C than in Class A and Class B in HBV-associated cirrhosis and HBV-associated HCC groups. The octadecadienyl carnitine level was higher in HBV-associated cirrhosis group than in other two groups. Serum levels of selected long-chain lysoPCs are promising markers for the progression of HBV-associated liver diseases.

Protein oxidation, nitration and glycation biomarkers for early-stage diagnosis of osteoarthritis of the knee and typing and progression of arthritic disease

Background

There is currently no blood-based test for detection of early-stage osteoarthritis (OA) and the anti-cyclic citrullinated peptide (CCP) antibody test for rheumatoid arthritis (RA) has relatively low sensitivity for early-stage disease. Morbidity in arthritis could be markedly decreased if early-stage arthritis could be routinely detected and classified by clinical chemistry test. We hypothesised that damage to proteins of the joint by oxidation, nitration and glycation, and with signatures released in plasma as oxidized, nitrated and glycated amino acids may facilitate early-stage diagnosis and typing of arthritis.

Methods

Patients with knee joint early-stage and advanced OA and RA or other inflammatory joint disease (non-RA) and healthy subjects with good skeletal health were recruited for the study (n = 225). Plasma/serum and synovial fluid was analysed for oxidized, nitrated and glycated proteins and amino acids by quantitative liquid chromatography-tandem mass spectrometry. Data-driven machine learning methods were employed to explore diagnostic utility of the measurements for detection and classifying early-stage OA and RA, non-RA and good skeletal health with training set and independent test set cohorts.

Results

Glycated, oxidized and nitrated proteins and amino acids were detected in synovial fluid and plasma of arthritic patients with characteristic patterns found in early and advanced OA and RA, and non-RA, with respect to healthy controls. In early-stage disease, two algorithms for consecutive use in diagnosis were developed: (1) disease versus healthy control, and (2) classification as OA, RA and non-RA. The algorithms featured 10 damaged amino acids in plasma, hydroxyproline and anti-CCP antibody status. Sensitivities/specificities were: (1) good skeletal health, 0.92/0.91; (2) early-stage OA, 0.92/0.90; early-stage RA, 0.80/0.78; and non-RA, 0.70/0.65 (training set). These were confirmed in independent test set validation. Damaged amino acids increased further in severe and advanced OA and RA.

Conclusions

Oxidized, nitrated and glycated amino acids combined with hydroxyproline and anti-CCP antibody status provided a plasma-based biochemical test of relatively high sensitivity and specificity for early-stage diagnosis and typing of arthritic disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-016-1154-3) contains supplementary material, which is available to authorized users.

Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd.

The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

Background

The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible.

Objective

The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and¹H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics.

Methods

Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,¹H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods.

Results

The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway.

Conclusions

We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and¹H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study.

Trial Registration

German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx)

Pregnancy-Related Changes of Amino Acid and Acylcarnitine Concentrations: The Impact of Obesity

Objective Our primary objective was to assess the difference in amino and fatty acid biomarkers throughout pregnancy in women with and without obesity. Interactions between biomarkers and obesity status for associations with maternal and fetal metabolic measures were secondarily analyzed. Methods Overall 39 women (15 cases, 24 controls) were enrolled in this study during their 15- to 20-weeks' visit at the University of Iowa Hospitals and Clinics. We analyzed 32 amino acid and acylcarnitine concentrations with tandem mass spectrometry for differences throughout pregnancy as well as among women with and without obesity (body mass index [BMI] ≥ 35, BMI < 25). Results There were substantial changes in amino acids and acylcarnitine metabolites between the second and third trimesters (nonfasting state) of pregnancy that were significant after correcting for multiple testing (p < 0.002). Examining differences by maternal obesity, C8:1 (second trimester) and C2, C4-OH, C18:1 (third trimester) were higher in women with obesity compared with women without obesity. Several metabolites were marginally (0.002 < p < 0.05) correlated with birth weight, maternal glucose, and maternal weight gain stratified by obesity status and trimester. Conclusions Understanding maternal metabolism throughout pregnancy and the influence of obesity is a critical step in identifying potential mechanisms that may contribute to adverse outcomes in pregnancies complicated by obesity.

Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program's goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. The complete set of training materials including slide sets and videos can be viewed at http://www.uab.edu/proteomics/metabolomics/workshop/workshop_june_2015.php. Copyright © 2016 John Wiley & Sons, Ltd.

Association of Plasma Small-Molecule Intermediate Metabolites With Age and Body Mass Index Across Six Diverse Study Populations

BACKGROUND

Older age and obesity are associated with metabolic dysregulation; the mechanism by which these factors impact metabolism across the lifespan is important, but relatively unknown. We evaluated a panel of amino acids (AAs) and acylcarnitines (ACs) to identify effects of age and adiposity (body mass index) on circulating small-molecule metabolites in a meta-analysis of six diverse study populations.

METHODS

Targeted metabolic profiling was performed in six independent studies, representing 739 subjects with a broad range of age, body mass index, health states, and ethnic origin. Principal components analysis was performed on log-normalized values for AAs and ACs separately, generating one AC factor and two AA factors for each study. A common AC factor consisted primarily of acetylcarnitine, medium-chain AC, and several long-chain AC. AA Factor 1 consisted primarily of large neutral AAs. Glycine was its own factor.

RESULTS

Metabolic profiling and factor analysis identified clusters of related metabolites of lipid and AA metabolism that were consistently associated with age and body mass in a series of studies with a broad range of age, body mass index, and health status. An inverse association of glycine with body mass index and male gender supports its role as a marker of favorable metabolic health.

CONCLUSIONS

An important focus of future investigations should be to determine whether these clusters of metabolic intermediates are possible early predictors of health outcomes associated with body mass; are involved with accelerated aging; are involved in the causative pathway of aging; and how modification of these metabolic pathways impact the biology of aging.

Ataxin-2 (Atxn2)-Knock-Out Mice Show Branched Chain Amino Acids and Fatty Acids Pathway Alterations

Human Ataxin-2 (ATXN2) gene locus variants have been associated with obesity, diabetes mellitus type 1,and hypertension in genome-wide association studies, whereas mouse studies showed the knock-out of Atxn2 to lead to obesity, insulin resistance, and dyslipidemia. Intriguingly, the deficiency of ATXN2 protein orthologs in yeast and flies rescues the neurodegeneration process triggered by TDP-43 and Ataxin-1 toxicity. To understand the molecular effects of ATXN2 deficiency by unbiased approaches, we quantified the global proteome and metabolome of Atxn2-knock-out mice with label-free mass spectrometry. In liver tissue, significant downregulations of the proteins ACADS, ALDH6A1, ALDH7A1, IVD, MCCC2, PCCA, OTC, together with bioinformatic enrichment of downregulated pathways for branched chain and other amino acid metabolism, fatty acids, and citric acid cycle were observed. Statistical trends in the cerebellar proteome and in the metabolomic profiles supported these findings. They are in good agreement with recent claims that PBP1, the yeast ortholog of ATXN2, sequestrates the nutrient sensor TORC1 in periods of cell stress. Overall, ATXN2 appears to modulate nutrition and metabolism, and its activity changes are determinants of growth excess or cell atrophy.

Enhanced acylcarnitine annotation in high-resolution mass spectrometry data: fragmentation analysis for the classification and annotation of acylcarnitines

Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software¹. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context of untargeted metabolomics experiments is a valuable tool to enhance the annotation of small metabolites.

Influence of Freezing and Storage Procedure on Human Urine Samples in NMR-Based Metabolomics

It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at -20 °C, on dry ice, at -80 °C or in liquid nitrogen and then stored at -20 °C, -80 °C or in liquid nitrogen vapor phase for 1-5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO2 concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at -20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.