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Background/aims: Having type 2 diabetes (T2D) in combination with being overweight results in an additional increase in cardiovascular disease (CVD) risk. In addition, T2D and obesity are associated with increased levels of total homocysteine (tHcy), possibly contributing to the CVD risk. Weight loss dieting has positive effects on several CVD risk factors, but whether it affects tHcy remains unclear. Therefore, the aim of this study was to determine the effect of a calorie restricted diet on tHcy in overweight people with T2D. Methods:In this post-hoc analysis of the POWER study, adults with T2D and a BMI greater than 27 kg/m² were included from the outpatient diabetes clinic of the Erasmus Medical Center, Rotterdam. The patients were subjected to a very low-calorie diet with fortified meal replacements for 20 weeks. Before and after this intervention, blood samples were collected to measure tHcy and other CVD risk factors like glycaemic and lipid parameters. Results: 161 overweight participants with T2D were included, with a mean age of 54 years (range 26–74), mean weight of 104.6 ± 19.9 kg and mean HbA1c of 62.7 ± 14.3 mmol/mol. At baseline, men displayed higher tHcy than women, and tHcy level was positively correlated with body weight and triglyceride levels, while it was negatively correlated with renal function and HDL cholesterol. During the intervention, bodyweight was reduced by a mean of 9.7% (from 104.6 ± 19.9 to 94.5 ± 18.1 kg p < 0.001), and all measured glycaemic and lipid blood parameters improved significantly. However, tHcy remained unchanged (from 12.1 ± 4.1 to 12.1 ± 4.2 umol/L, p = 0.880). The change in tHcy during the intervention was negatively associated with the change in weight and BMI (p = 0.01 and p = 0.008, respectively). People who lost < 10 kg (n = 92) had a mean tHcy change of -0.47 umol/L, while people who lost more than ≥ 10 kg (n = 69) had a mean tHcy change of 0.60 um

Two siblings, presenting with a neurometabolic phenotype, were identified with 5, 10-methenyltetrahydrofolate synthetase (MTHFS) deficiency. Whole genome sequencing in both patients demonstrated an homozygous MTHFS variant NM_006441.3(MTHFS):c.434G > A, p.Arg145Gin, which has been described before. At baseline, both patients showed moderate hyperhomocysteinemia, decreased 5-methyltetrahydrofolate (5MTHF), and increased 5-formyltetrahydrofolate (5-FTHF) in whole blood. In CSF, 5MTHF levels were in the low-normal range and 5-FTHF was strongly increased. In our novel enzyme assay, MTHFS activity was deficient in cultured fibroblasts in both sisters. Oral treatment was initiated with escalating dose of 5-methyltetrahydrofolate (5MTHF) up to 12 mg and hydroxycobalamin 5 mg daily. Plasma homocysteine normalized and 5MTHF became elevated in the blood of both patients. The elevated 5FTHF levels increased further on treatment in blood and CSF. This regimen resulted in some clinical improvement of patient 1. In patient 2, the clinical benefits of 5MTHF supplementation were less obvious. It seems plausible that the alleviation of the deficient 5MTHF levels and normalization of homocysteine in blood are of some clinical benefit. On the other hand, the very high levels of 5FTHF may well be detrimental and may prompt us to decrease the dose of 5MTHF. In addition, we hypothesize that the crippled MTHFS enzyme may destabilize the purinosome, which is presumably not ameliorated by 5MTHF.

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Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detect IEM patient profiles. We benchmarked 30 different outlier detection methods when applied to three untargeted metabolomics datasets. Our results show great differences in IEM detection performances across the various methods. The methods DeepSVDD and R-graph performed most consistently across the three metabolomics datasets. For datasets with a more balanced number of samples-to-features ratio, we found that AE reconstruction error, Mahalanobis and PCA reconstruction error also performed well. Furthermore, we demonstrated the importance of a PCA transform prior to applying an outlier detection method since we observed that this increases the performance of several outlier detection methods. For only one of the three metabolomics datasets, we observed clinically satisfying performances for some outlier detection methods, where we were able to detect 90% of the IEM patient samples while detecting no false positives. These results suggest that outlier detection methods have the potential to aid the clinical investigator in routine screening for IEM using untargeted metabolomics data, but also show that further improvements are needed to ensure clinically satisfying performances., Pattern Recognition and Bioinformatics

The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing genetic variant(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in genes associated with metabolic processes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 81% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with Combined Annotation Dependent Depletion (CADD) scores (a measure for gene variant deleteriousness) and ranked the metabolic genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the genes containing the disease-causing variant when compared with the two approaches individually. For 15/27 IEM patients the correct affected gene was ranked within the top 0.25% of the set of potentially affected genes. Together, our findings suggest that metabolomics data improves the identification of affected genes in patients suffering from IEM., Pattern Recognition and Bioinformatics

The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing genetic variant(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in genes associated with metabolic processes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 81% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with Combined Annotation Dependent Depletion (CADD) scores (a measure for gene variant deleteriousness) and ranked the metabolic genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the genes containing the disease-causing variant when compared with the two approaches individually. For 15/27 IEM patients the correct affected gene was ranked within the top 0.25% of the set of potentially affected genes. Together, our findings suggest that metabolomics data improves the identification of affected genes in patients suffering from IEM.

The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing genetic variant(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in genes associated with metabolic processes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 81% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with Combined Annotation Dependent Depletion (CADD) scores (a measure for gene variant deleteriousness) and ranked the metabolic genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the genes containing the disease-causing variant when compared with the two approaches individually. For 15/27 IEM patients the correct affected gene was ranked within the top 0.25% of the set of potentially affected genes. Together, our findings suggest that metabolomics data improves the identification of affected genes in patients suffering from IEM., Pattern Recognition and Bioinformatics

One-carbon metabolism (1C metabolism) is of paramount importance for cell metabolism and mammalian development. It is involved in the synthesis or modification of a wide variety of compounds such as proteins, lipids, purines, nucleic acids and neurotransmitters. We describe here the evolution of expression of genes related to 1C metabolism during liver and brain ontogeny in mouse. The level of expression of 30 genes involved in 1C metabolism was quantified by RT-qPCR in liver and brain tissues of OF1 mice at E9, E11, E13, E15, E17, P0, P3, P5, P10, P15 developmental stages and in adults. In the liver, hierarchical clustering of the gene expression patterns revealed five distinct clades of genes with a first bifurcating hierarchy distinguishing two main developmental stages before and after E15. In the brain most of the 1C metabolism genes are expressed but at a lower levels. The gene expression of enzymes involved in 1C metabolism show dramatic changes during development that are tissue specific. mRNA expression patterns of all major genes involved in 1C metabolism in liver and brain provide clues about the methylation demand and methylation pathways during embryonic development.

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer, a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5–37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy., Pattern Recognition and Bioinformatics

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer, a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5–37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy., Pattern Recognition and Bioinformatics

Classical homocystinuria (HCU) is the most common inborn error of metabolism in Qatar, with an incidence of 1:1800, and is caused by the Qatari founder p.R336C mutation in the CBS gene. This study describes the natural history and clinical manifestations of HCU in the Qatari population. A single center study was performed between 2016 and 2017 in 126 Qatari patients, from 82 families. Detailed clinical and biochemical data were collected, and Stanford-Binet intelligence, quality of life and adherence to treatment assessments were conducted prospectively. Patients were assigned to one of three groups, according to the mode of diagnosis: (a) late diagnosis group (LDG), (b) family screening group (FSG), and (c) newborn screening group (NSG). Of the 126 patients, 69 (55%) were in the LDG, 44 (35%) in the NSG, and 13 (10%) in the FSG. The leading factors for diagnosis in the LDG were ocular manifestations (49%), neurological manifestations (45%), thromboembolic events (4%), and hyperactivity and behavioral changes (1%). Both FSG and NSG groups were asymptomatic at time of diagnosis. NSG had significantly higher intelligence quotient, quality of life, and adherence values compared with the LDG. The LDG and FSG had significantly higher methionine levels than the NSG. The LDG also had significantly higher total homocysteine levels than the NSG and FSG. Regression analysis confirmed these results even when adjusting for age at diagnosis, current age, or adherence. These findings increase the understanding of the natural history of HCU and highlight the importance of early diagnosis and treatment. SYNOPSIS: A study in 126 Qatari patients with HCU, including biochemical, clinical, and other key assessments, reveals that patients with a late clinical diagnosis have a poorer outcome, hereby highlighting the importance of early diagnosis and treatment.

Background: Disturbances in the levels of one-carbon (1C) metabolism metabolites have been associated with a wide variety of neuropsychiatric diseases. Cerebrospinal fluid (CSF) levels of homocysteine (Hcy) and the other 1C metabolites, nor their interrelatedness and putative determinants, have been studied extensively in a healthy population. Methods: Plasma and CSF samples from 100 individuals free from neuropsychiatric diseases were analyzed (55 male, 45 female; age 50±17 years). In blood, we measured plasma Hcy, serum folate and serum vitamin B12. In CSF, we measured total Hcy, S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH) and 5-methyltetrahydrofolate (5-methylTHF). Highly selective analytical methods like liquid chromatography combined with either mass spectrometry or fluorescence detection were used. Results: CSF Hcy was inversely correlated with CSF 5-methylTHF and positively with plasma Hcy, independent of serum folate status. CSF SAH correlated with age, lower CSF 5-methylTHF and higher CSF Hcy. CSF 5-methylTHF showed independent negative correlations with age and positive correlations with serum folate. CSF SAM did not correlate with any of the 1C metabolites. Conclusions: Aging is characterized by a reduction in CSF 5-methylTHF levels and increased CSF levels of the potentially neurotoxic transmethylation inhibitor SAH. CSF 5-methylTHF, which is itself determined in part by systemic folate status, is a powerful independent determinant of CSF levels of Hcy and SAH

Background: This paper summarizes the results of a group effort to bring together the worldwide available data on patients who are either homozygotes or compound heterozygotes for mutations in MAT1A. MAT1A encodes the subunit that forms two methionine adenosyltransferase isoenzymes, tetrameric MAT I and dimeric MAT III, that catalyze the conversion of methionine and ATP to S-adenosylmethionine (AdoMet). Subnormal MAT I/III activity leads to hypermethioninemia. Individuals, with hypermethioninemia due to one of the MAT1A mutations that in heterozygotes cause relatively mild and clinically benign hypermethioninemia are currently often being flagged in screening programs measuring methionine elevation to identify newborns with defective cystathionine beta-synthase activity. Homozygotes or compound heterozygotes for MAT1A mutations are less frequent. Some but not all, such individuals have manifested demyelination or other CNS abnormalities. Purpose of the study: The goals of the present effort have been to determine the frequency of such abnormalities, to find how best to predict whether they will occur, and to evaluate the outcomes of the variety of treatment regimens that have been used. Data have been gathered for 64 patients, of whom 32 have some evidence of CNS abnormalities (based mainly on MRI findings), and 32 do not have such evidence. Results and Discussion: The results show that mean plasma methionine concentrations provide the best indication of the group into which a given patient will fall: those with means of 800 mu M or higher usually have evidence of CNS abnormalities, whereas those with lower means usually do not. Data are reported for individual patients for MAT1A genotypes, plasma methionine, total homocysteine (tHcy), and AdoMet concentrations, liver function studies, results of 15 pregnancies, and the outcomes of dietary methionine restriction and/or AdoMet supplementation. Possible pathophysiological mechanisms that might contribute to CNS damage

Background: This paper summarizes the results of a group effort to bring together the worldwide available data on patients who are either homozygotes or compound heterozygotes for mutations in MAT1A. MAT1A encodes the subunit that forms two methionine adenosyltransferase isoenzymes, tetrameric MAT I and dimeric MAT III, that catalyze the conversion of methionine and ATP to S-adenosylmethionine (AdoMet). Subnormal MAT I/III activity leads to hypermethioninemia. Individuals, with hypermethioninemia due to one of the MAT1A mutations that in heterozygotes cause relatively mild and clinically benign hypermethioninemia are currently often being flagged in screening programs measuring methionine elevation to identify newborns with defective cystathionine beta-synthase activity. Homozygotes or compound heterozygotes for MAT1A mutations are less frequent. Some but not all, such individuals have manifested demyelination or other CNS abnormalities. Purpose of the study: The goals of the present effort have been to determine the frequency of such abnormalities, to find how best to predict whether they will occur, and to evaluate the outcomes of the variety of treatment regimens that have been used. Data have been gathered for 64 patients, of whom 32 have some evidence of CNS abnormalities (based mainly on MRI findings), and 32 do not have such evidence. Results and Discussion: The results show that mean plasma methionine concentrations provide the best indication of the group into which a given patient will fall: those with means of 800 mu M or higher usually have evidence of CNS abnormalities, whereas those with lower means usually do not. Data are reported for individual patients for MAT1A genotypes, plasma methionine, total homocysteine (tHcy), and AdoMet concentrations, liver function studies, results of 15 pregnancies, and the outcomes of dietary methionine restriction and/or AdoMet supplementation. Possible pathophysiological mechanisms that might contribute to CNS damage

Background: This paper summarizes the results of a group effort to bring together the worldwide available data on patients who are either homozygotes or compound heterozygotes for mutations in MAT1A. MAT1A encodes the subunit that forms two methionine adenosyltransferase isoenzymes, tetrameric MAT I and dimeric MAT III, that catalyze the conversion of methionine and ATP to S-adenosylmethionine (AdoMet). Subnormal MAT I/III activity leads to hypermethioninemia. Individuals, with hypermethioninemia due to one of the MAT1A mutations that in heterozygotes cause relatively mild and clinically benign hypermethioninemia are currently often being flagged in screening programs measuring methionine elevation to identify newborns with defective cystathionine beta-synthase activity. Homozygotes or compound heterozygotes for MAT1A mutations are less frequent. Some but not all, such individuals have manifested demyelination or other CNS abnormalities. Purpose of the study: The goals of the present effort have been to determine the frequency of such abnormalities, to find how best to predict whether they will occur, and to evaluate the outcomes of the variety of treatment regimens that have been used. Data have been gathered for 64 patients, of whom 32 have some evidence of CNS abnormalities (based mainly on MRI findings), and 32 do not have such evidence. Results and Discussion: The results show that mean plasma methionine concentrations provide the best indication of the group into which a given patient will fall: those with means of 800 mu M or higher usually have evidence of CNS abnormalities, whereas those with lower means usually do not. Data are reported for individual patients for MAT1A genotypes, plasma methionine, total homocysteine (tHcy), and AdoMet concentrations, liver function studies, results of 15 pregnancies, and the outcomes of dietary methionine restriction and/or AdoMet supplementation. Possible pathophysiological mechanisms that might contribute to CNS damage

Background: This paper summarizes the results of a group effort to bring together the worldwide available data on patients who are either homozygotes or compound heterozygotes for mutations in MAT1A. MAT1A encodes the subunit that forms two methionine adenosyltransferase isoenzymes, tetrameric MAT I and dimeric MAT III, that catalyze the conversion of methionine and ATP to S-adenosylmethionine (AdoMet). Subnormal MAT I/III activity leads to hypermethioninemia. Individuals, with hypermethioninemia due to one of the MAT1A mutations that in heterozygotes cause relatively mild and clinically benign hypermethioninemia are currently often being flagged in screening programs measuring methionine elevation to identify newborns with defective cystathionine beta-synthase activity. Homozygotes or compound heterozygotes for MAT1A mutations are less frequent. Some but not all, such individuals have manifested demyelination or other CNS abnormalities. Purpose of the study: The goals of the present effort have been to determine the frequency of such abnormalities, to find how best to predict whether they will occur, and to evaluate the outcomes of the variety of treatment regimens that have been used. Data have been gathered for 64 patients, of whom 32 have some evidence of CNS abnormalities (based mainly on MRI findings), and 32 do not have such evidence. Results and Discussion: The results show that mean plasma methionine concentrations provide the best indication of the group into which a given patient will fall: those with means of 800 mu M or higher usually have evidence of CNS abnormalities, whereas those with lower means usually do not. Data are reported for individual patients for MAT1A genotypes, plasma methionine, total homocysteine (tHcy), and AdoMet concentrations, liver function studies, results of 15 pregnancies, and the outcomes of dietary methionine restriction and/or AdoMet supplementation. Possible pathophysiological mechanisms that might contribute to CNS damage

Newborn screening (NBS) is justified if early intervention is effective in a disorder generally not detected early in life on a clinical basis, and if sensitive and specific biochemical markers exist. Experience with NBS for homocystinurias and methylation disorders is limited. However, there is robust evidence for the success of early treatment with diet, betaine and/or pyridoxine for CBS deficiency and good evidence for the success of early betaine treatment in severe MTHFR deficiency. These conditions can be screened in dried blood spots by determining methionine (Met), methionine-to-phenylanine (Met/Phe) ratio, and total homocysteine (tHcy) as a second tier marker. Therefore, we recommend NBS for cystathionine beta-synthase and severe MTHFR deficiency. Weaker evidence is available for the disorders of intracellular cobalamin metabolism. Early treatment is clearly of advantage for patients with the late-onset cblC defect. In the early-onset type, survival and non-neurological symptoms improve but the effect on neurocognitive development is uncertain. The cblC defect can be screened by measuring propionylcarnitine, propionylcarnitine-to-acetylcarnitine ratio combined with the second tier markers methylmalonic acid and tHcy. For the cblE and cblG defects, evidence for the benefit of early treatment is weaker; and data on performance of Met, Met/Phe and tHcy even more limited. Individuals homozygous or compound heterozygous for MAT1A mutations may benefit from detection by NBS using Met, which on the other hand also detects asymptomatic heterozygotes. Clinical and laboratory data is insufficient to develop any recommendation on NBS for the cblD, cblF, cblJ defects, glycineN-methyltransferase-, S-adenosylhomocysteinehydrolase- and adenosine kinase deficiency.

Background: This paper summarizes the results of a group effort to bring together the worldwide available data on patients who are either homozygotes or compound heterozygotes for mutations in MAT1A. MAT1A encodes the subunit that forms two methionine adenosyltransferase isoenzymes, tetrameric MAT I and dimeric MAT III, that catalyze the conversion of methionine and ATP to S-adenosylmethionine (AdoMet). Subnormal MAT I/III activity leads to hypermethioninemia. Individuals, with hypermethioninemia due to one of the MAT1A mutations that in heterozygotes cause relatively mild and clinically benign hypermethioninemia are currently often being flagged in screening programs measuring methionine elevation to identify newborns with defective cystathionine beta-synthase activity. Homozygotes or compound heterozygotes for MAT1A mutations are less frequent. Some but not all, such individuals have manifested demyelination or other CNS abnormalities. Purpose of the study: The goals of the present effort have been to determine the frequency of such abnormalities, to find how best to predict whether they will occur, and to evaluate the outcomes of the variety of treatment regimens that have been used. Data have been gathered for 64 patients, of whom 32 have some evidence of CNS abnormalities (based mainly on MRI findings), and 32 do not have such evidence. Results and Discussion: The results show that mean plasma methionine concentrations provide the best indication of the group into which a given patient will fall: those with means of 800 mu M or higher usually have evidence of CNS abnormalities, whereas those with lower means usually do not. Data are reported for individual patients for MAT1A genotypes, plasma methionine, total homocysteine (tHcy), and AdoMet concentrations, liver function studies, results of 15 pregnancies, and the outcomes of dietary methionine restriction and/or AdoMet supplementation. Possible pathophysiological mechanisms that might contribute to CNS damage

Production of the endogenous vasodilator nitric oxide (NO) from L-arginine by NO synthase is modulated by L-homoarginine, L-monomethylargine (MMA), asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA). Here we report on a stable isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) method for simultaneous determination of these metabolites in plasma, cells and tissues. After addition of the internal standards (D-7-ADMA, D-4-L-homoarginine and C-13(6)-Larginine), analytes were extracted from the samples using Waters Oasis MCX solid phase extraction cartridges. Butylated analytes were separated isocratically on a Waters XTerra MS C18 column (3.5 mu m. 3.9 mm x 100 mm) using 600 mg/L ammonium formate in water - acetonitrile (95.5:4.5, v/v) containing 0.1 vol% formic acid, and subsequently measured on an AB Sciex API 3000 triple quadrupole mass spectrometer. Multiple reaction monitoring in positive mode was used for analyte quantification. Validation was performed in plasma. Calibration lines were linear (r(2) >= 0.9979) and lower limits of quantification in plasma were 0.4 nM for ADMA and SDMA and 0.8 nM for the other analytes. Accuracy (% bias) was <3% except for MMA (<7%), intra-assay precision (expressed as CV) was <3.5%, inter-assay precision <9.6%, and recovery 92.9-103.2% for all analytes. The method showed good correlation (r(2) >= 0.9125) with our previously validated HPLC-fluorescence method for measurement in plasma, and was implemented with good performance for measurement of tissue samples. Application of the method revealed the remarkably fast (i.e. within 60 min) appearance in plasma of stable isotope-labeled ADMA, SDMA, and MMA during infusion of D-3-methyl-1-C-13-methionine in healthy volunteers.

Four inborn errors of metabolism (IEMs) are known to cause hypermethioninemia by directly interfering with the methionine cycle. Hypermethioninemia is occasionally discovered incidentally, but it is often disregarded as an unspecific finding, particularly if liver disease is involved. In many individuals the hypermethioninemia resolves without further deterioration, but it can also represent an early sign of a severe, progressive neurodevelopmental disorder. Further investigation of unclear hypermethioninemia is therefore important. We studied two siblings affected by severe developmental delay and liver dysfunction. Biochemical analysis revealed increased plasma levels of methionine, S-adenosylmethionine (Ado Met), and S-adenosylhomocysteine (AdoHcy) but normal or mildly elevated homocysteine (Hcy) levels, indicating a block in the methionine cycle. We excluded S-adenosylhomocysteine hydrolase (SAHH) deficiency, which causes a similar biochemical phenotype, by using genetic and biochemical techniques and hypothesized that there was a functional block in the SAHH enzyme as a result of a recessive mutation in a different gene. Using exome sequencing, we identified a homozygous c.902C>A (p.Ala301Glu) missense mutation in the adenosine kinase gene (ADK), the function of which fits perfectly with this hypothesis. Increased urinary adenosine excretion confirmed ADK deficiency in the siblings. Four additional individuals from two unrelated families with a similar presentation were identified and shown to have a homozygous c.653A>C (p.Asp218Ala) and c.38G>A (p.Gly13Glu) mutation, respectively, in the same gene. All three missense mutations were deleterious, as shown by activity measurements on recombinant enzymes. ADK deficiency is a previously undescribed, severe IEM shedding light on a functional link between the methionine cycle and adenosine metabolism.

Four inborn errors of metabolism (IEMs) are known to cause hypermethioninemia by directly interfering with the methionine cycle. Hypermethioninemia is occasionally discovered incidentally, but it is often disregarded as an unspecific finding, particularly if liver disease is involved. In many individuals the hypermethioninemia resolves without further deterioration, but it can also represent an early sign of a severe, progressive neurodevelopmental disorder. Further investigation of unclear hypermethioninemia is therefore important. We studied two siblings affected by severe developmental delay and liver dysfunction. Biochemical analysis revealed increased plasma levels of methionine, S-adenosylmethionine (Ado Met), and S-adenosylhomocysteine (AdoHcy) but normal or mildly elevated homocysteine (Hcy) levels, indicating a block in the methionine cycle. We excluded S-adenosylhomocysteine hydrolase (SAHH) deficiency, which causes a similar biochemical phenotype, by using genetic and biochemical techniques and hypothesized that there was a functional block in the SAHH enzyme as a result of a recessive mutation in a different gene. Using exome sequencing, we identified a homozygous c.902C>A (p.Ala301Glu) missense mutation in the adenosine kinase gene (ADK), the function of which fits perfectly with this hypothesis. Increased urinary adenosine excretion confirmed ADK deficiency in the siblings. Four additional individuals from two unrelated families with a similar presentation were identified and shown to have a homozygous c.653A>C (p.Asp218Ala) and c.38G>A (p.Gly13Glu) mutation, respectively, in the same gene. All three missense mutations were deleterious, as shown by activity measurements on recombinant enzymes. ADK deficiency is a previously undescribed, severe IEM shedding light on a functional link between the methionine cycle and adenosine metabolism., QC 20111107

[EN] The association between the BTD genotype and biochemical phenotype [profound biotinidase deficiency (BD), partial BD or heterozygous activity] is not always consistent. This study aimed to investigate the genotype-biochemical phenotype association in patients with low biotinidase activity. Methods All exons, the 5'UTR and the promoter of the BTD gene were sequenced in 72 Brazilian individuals who exhibited low biotinidase activity. For each patient, the expected biochemical phenotype based on the known genotype was compared with the observed biochemical phenotype. Additional non-genetic factors that could affect the biotinidase activity were also analysed. Most individuals were identified by neonatal screening (n = 66/72). When consecutive results for the same patient were compared, age, prematurity and neonatal jaundice appeared to affect the level of biotinidase activity. The biochemical phenotype at the time of the second blood collection changed in 11/22 patients compared to results from the first sample. Three novel variants were found: c.1337T>C (p.L446P), c.1466A>G (p.N489S) and c.962G>A (p.W321*). Some patients with the same genotype presented different biochemical phenotypes. The expected and observed biochemical phenotypes agreed in 68.5% of cases (concordant patients). The non-coding variants c.-183G>A, c.-315A>G and c.-514C>T were present in heterozygosis in 5/17 discordant patients. In addition, c.- 183G>A and c.-514C>T were also present in 10/37 concordant patients. The variants found in the promoter region do not appear to have a strong impact on biotinidase activity. Since there is a disparity between the BTD genotype and biochemical phenotype, and biotinidase activity may be affected by both genetic and non-genetic factors, we suggest that the diagnosis of BD should be based on more than one measurement of plasma biotinidase activity. DNA analysis can be of additional relevance to differentiate between partial BD and heterozygosity.

Background: Disturbances in the levels of one-carbon (1C) metabolism metabolites have been associated with a wide variety of neuropsychiatric diseases. Cerebrospinal fluid (CSF) levels of homocysteine (Hcy) and the other 1C metabolites, nor their interrelatedness and putative determinants, have been studied extensively in a healthy population. Methods: Plasma and CSF samples from 100 individuals free from neuropsychiatric diseases were analyzed (55 male, 45 female; age 50±17 years). In blood, we measured plasma Hcy, serum folate and serum vitamin B12. In CSF, we measured total Hcy, S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH) and 5-methyltetrahydrofolate (5-methylTHF). Highly selective analytical methods like liquid chromatography combined with either mass spectrometry or fluorescence detection were used. Results: CSF Hcy was inversely correlated with CSF 5-methylTHF and positively with plasma Hcy, independent of serum folate status. CSF SAH correlated with age, lower CSF 5-methylTHF and higher CSF Hcy. CSF 5-methylTHF showed independent negative correlations with age and positive correlations with serum folate. CSF SAM did not correlate with any of the 1C metabolites. Conclusions: Aging is characterized by a reduction in CSF 5-methylTHF levels and increased CSF levels of the potentially neurotoxic transmethylation inhibitor SAH. CSF 5-methylTHF, which is itself determined in part by systemic folate status, is a powerful independent determinant of CSF levels of Hcy and SAH