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1.
Tafadzwa Chihanga Sarah M. Hausmann Shuisong Ni Michael A. Kennedy 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):28
Introduction
Comparative metabolic profiling of different human cancer cell lines can reveal metabolic pathways up-regulated or down-regulated in each cell line, potentially providing insight into distinct metabolism taking place in different types of cancer cells. It is noteworthy, however, that human cell lines available from public repositories are deposited with recommended media for optimal growth, and if cell lines to be compared are cultured on different growth media, this introduces a potentially serious confounding variable in metabolic profiling studies designed to identify intrinsic metabolic pathways active in each cell line.Objectives
The goal of this study was to determine if the culture media used to grow human cell lines had a significant impact on the measured metabolic profiles.Methods
NMR-based metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, AsPC-1, MiaPaCa-2 and Panc-1, were compared after culture on Dulbecco’s Modified Eagle Medium (DMEM) or Roswell Park Memorial Institute (RPMI-1640) medium.Results
Comparisons of the same cell lines cultured on different media revealed that the concentrations of many metabolites depended strongly on the choice of culture media. Analyses of different cell lines grown on the same media revealed insight into their metabolic differences.Conclusion
The choice of culture media can significantly impact metabolic profiles of human cell lines and should be considered an important variable when designing metabolic profiling studies. Also, the metabolic differences of cells cultured on media recommended for optimal growth in comparison to a second growth medium can reveal critical insight into metabolic pathways active in each cell line.2.
Daqiang Pan Caroline Lindau Simon Lagies Nils Wiedemann Bernd Kammerer 《Metabolomics : Official journal of the Metabolomic Society》2018,14(5):59
Introduction
Subcellular compartmentalization enables eukaryotic cells to carry out different reactions at the same time, resulting in different metabolite pools in the subcellular compartments. Thus, mutations affecting the mitochondrial energy metabolism could cause different metabolic alterations in mitochondria compared to the cytoplasm. Given that the metabolite pool in the cytosol is larger than that of other subcellular compartments, metabolic profiling of total cells could miss these compartment-specific metabolic alterations.Objectives
To reveal compartment-specific metabolic differences, mitochondria and the cytoplasmic fraction of baker’s yeast Saccharomyces cerevisiae were isolated and subjected to metabolic profiling.Methods
Mitochondria were isolated through differential centrifugation and were analyzed together with the remaining cytoplasm by gas chromatography–mass spectrometry (GC–MS) based metabolic profiling.Results
Seventy-two metabolites were identified, of which eight were found exclusively in mitochondria and sixteen exclusively in the cytoplasm. Based on the metabolic signature of mitochondria and of the cytoplasm, mutants of the succinate dehydrogenase (respiratory chain complex II) and of the FOF1-ATP-synthase (complex V) can be discriminated in both compartments by principal component analysis from wild-type and each other. These mitochondrial oxidative phosphorylation machinery mutants altered not only citric acid cycle related metabolites but also amino acids, fatty acids, purine and pyrimidine intermediates and others.Conclusion
By applying metabolomics to isolated mitochondria and the corresponding cytoplasm, compartment-specific metabolic signatures can be identified. This subcellular metabolomics analysis is a powerful tool to study the molecular mechanism of compartment-specific metabolic homeostasis in response to mutations affecting the mitochondrial metabolism.3.
Leonie Venter Du Toit Loots Lodewyk Japie Mienie Peet J. Jansen van Rensburg Shayne Mason Andre Vosloo Jeremie Zander Lindeque 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):49
Introduction
Oxygen is essential for metabolic processes and in the absence thereof alternative metabolic pathways are required for energy production, as seen in marine invertebrates like abalone. Even though hypoxia has been responsible for significant losses to the aquaculture industry, the overall metabolic adaptations of abalone in response to environmental hypoxia are as yet, not fully elucidated.Objective
To use a multiplatform metabolomics approach to characterize the metabolic changes associated with energy production in abalone (Haliotis midae) when exposed to environmental hypoxia.Methods
Metabolomics analysis of abalone adductor and foot muscle, left and right gill, hemolymph, and epipodial tissue samples were conducted using a multiplatform approach, which included untargeted NMR spectroscopy, untargeted and targeted LC–MS spectrometry, and untargeted and semi-targeted GC-MS spectrometric analyses.Results
Increased levels of anaerobic end-products specific to marine animals were found which include alanopine, strombine, tauropine and octopine. These were accompanied by elevated lactate, succinate and arginine, of which the latter is a product of phosphoarginine breakdown in abalone. Primarily amino acid metabolism was affected, with carbohydrate and lipid metabolism assisting with anaerobic energy production to a lesser extent. Different tissues showed varied metabolic responses to hypoxia, with the largest metabolic changes in the adductor muscle.Conclusions
From this investigation, it becomes evident that abalone have well-developed (yet understudied) metabolic mechanisms for surviving hypoxic periods. Furthermore, metabolomics serves as a powerful tool for investigating the altered metabolic processes in abalone.4.
Jie Yang Jianhua Cheng Bo Sun Haijing Li Shengming Wu Fangting Dong Xianzhong Yan 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):40
Introduction
Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.Objectives
Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.Methods
Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.Results
Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.Conclusion
The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.5.
Shamima Akter Subrina Jesmin Md. Mizanur Rahman Md. Majedul Islam Most. Tanzila Khatun Naoto Yamaguchi Hidechika Akashi Taro Mizutani 《PloS one》2013,8(8)
Background
Parity increases the risk for coronary heart disease; however, its association with metabolic syndrome among women in low-income countries is still unknown.Objective
This study investigates the association between parity or gravidity and metabolic syndrome in rural Bangladeshi women.Methods
A cross-sectional study was conducted in 1,219 women aged 15–75 years from rural Bangladesh. Metabolic syndrome was defined according to the standard NCEP-ATP III criteria. Logistic regression was used to estimate the association between parity and gravidity and metabolic syndrome, with adjustment of potential confounding variables.Results
Subjects with the highest gravidity (> = 4) had 1.66 times higher odds of having metabolic syndrome compared to those in the lowest gravidity (0-1) (P trend = 0.02). A similar association was found between parity and metabolic syndrome (P trend = 0.04), i.e., subjects in the highest parity (> = 4) had 1.65 times higher odds of having metabolic syndrome compared to those in the lowest parity (0-1). This positive association of parity and gravidity with metabolic syndrome was confined to pre-menopausal women (P trend <0.01). Among the components of metabolic syndrome only high blood pressure showed positive association with parity and gravidity (P trend = 0.01 and <0.001). Neither Parity nor gravidity was appreciably associated with other components of metabolic syndrome.Conclusions
Multi parity or gravidity may be a risk factor for metabolic syndrome. 相似文献6.
Norio Sugawara Norio Yasui-Furukori Manabu Yamazaki Kazutaka Shimoda Takao Mori Takuro Sugai Yutaro Suzuki Toshiyuki Someya 《PloS one》2014,9(1)
Background
There is growing concern about the metabolic abnormalities in patients with schizophrenia.Aims
The aim of this study was to assess the attitudes of psychiatrists toward metabolic adverse events in patients with schizophrenia.Method
A brief questionnaire was constructed to cover the following broad areas: the psychiatrists'' recognition of the metabolic risk of antipsychotic therapy, pattern of monitoring patients for physical risks, practice pattern for physical risks, and knowledge of metabolic disturbance. In March 2012, the questionnaire was mailed to 8,482 psychiatrists who were working at hospitals belonging to the Japan Psychiatric Hospitals Association.Results
The overall response rate was 2,583/8,482 (30.5%). Of the respondents, 85.2% (2,200/2,581) reported that they were concerned about prescribing antipsychotics that have a risk of elevating blood sugar; 47.6% (1,201/2,524) stated that their frequency of monitoring patients under antipsychotic treatment was based on their own experiences; and only 20.6% (5,22/2,534) of respondents answered that the frequency with which they monitored their patients was sufficient to reduce the metabolic risks.Conclusions
Psychiatrists practicing in Japan were generally aware and concerned about the metabolic risks for patients being treated with antipsychotics. Although psychiatrists should monitor their patients for metabolic abnormalities to balance these risks, a limited number of psychiatrists answered that the frequency with which they monitored patients to reduce the metabolic risks was sufficient. Promotion of the best practices of pharmacotherapy and monitoring is needed for psychiatrists treating patients with schizophrenia. 相似文献7.
Emily G. Armitage Andrew D. Southam 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):146
Introduction
Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.Objectives
Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.Methods
A literature search of the current relevant primary research was performed.Results
Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.Conclusion
Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.8.
Antonella Del-Corso Mario Cappiello Roberta Moschini Francesco Balestri Umberto Mura 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):2
Introduction
While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.Objectives
Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.Methods
The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.Results
Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.Conclusions
Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.9.
Ákos Kenéz Sven Dänicke Ulrike Rolle-Kampczyk Martin von Bergen Korinna Huber 《Metabolomics : Official journal of the Metabolomic Society》2016,12(11):165
Introduction
Dairy cows experience metabolic stress during the transition from late pregnancy to early lactation, due to the complex adaptation processes affecting energy homeostasis in support of milk production, collectively referred to as homeorhesis. According to the individual efficiency of this adaptation, some cows develop severe metabolic diseases while others are able to maintain metabolic health.Objectives
This study aimed to characterize patterns and changes of metabolic phenotype during the transition period, and to identify how far different metabolic pathways are affected by or contributing to the complex system of homeorhesis.Methods
Blood samples were collected from 26 German Holstein cows, repeatedly during the transition period: 42 and 10 days before calving and 3, 21 and 100 days after calving. Blood serum samples were subjected to a liquid chromatography–mass spectrometry based targeted metabolomics analysis using the AbsoluteIDQ p180 Kit of Biocrates Life Science AG (Innsbruck, Austria). Processed metabolomics data were evaluated by multivariate data analysis techniques such as principal component analysis (PCA) and partial least squares-discriminant analysis and by heatmap visualization.Results
The PCA revealed a clear separation according to sampling days, indicating a notable shift of the metabolic phenotype during the transition period. The heatmap showed that acylcarnitines provided a consistent clustering within sampling days, while the concentration of glycerophospholipids and sphingolipids were remarkably decreased 10 days before and 3 days after calving than earlier and later in the transition period.Conclusion
Analyzing longitudinal changes of the blood metabolome and identifying new biomarkers by this approach can help understanding the multifaceted metabolic adaptation of transition dairy cows.10.
Joana Pinto Sílvia O. Diaz Elisabete Aguiar Daniela Duarte António S. Barros Eulália Galhano Cristina Pita Maria do Céu Almeida Isabel M. Carreira Manfred Spraul Ana M. Gil 《Metabolomics : Official journal of the Metabolomic Society》2016,12(6):105
Introduction
The clinical management of Gestational diabetes mellitus (GDM) would benefit from enhanced metabolic knowledge both at the time of diagnosis and during therapy.Objectives
This work aimed at unveiling metabolic markers of GDM and of the subjects’ response to therapy.Methods
Urine NMR metabolomics was used with a variable selection methodology to reduce uninformative variability. The NMR data was analysed by multivariate and univariate analysis methodologies.Results
The results showed that urine NMR metabolomics enables a metabolic signature of GDM to be identified at the time of diagnosis. This signature comprises relevant changes in 12 NMR metabolites/resonances and qualitative variations in a number of additional metabolites. The metabolite changes characterizing GDM suggest adaptations in a number of different pathways and highlight the relevance of gut microflora disturbances in relation to the disease. The impact of diet and insulin treatments on the excreted metabolome of pregnant GDM women was measured and enabled responsive and resistant metabolic pathways to be identified, as well as side-effects of treatment i.e. metabolic changes induced by treatment and previously unrelated to the disease (including changes in the gut microflora). Furthermore, treatment duration was found to be associated to urine metabolic profile, thus emphasizing the possible future use of urine metabolomics in treatment follow-up and efficacy evaluation. Finally, a possible association of a priori urinary metabolome with future treatment requirements is reported, albeit requiring demonstration in larger cohorts. This result supports the hypothesis of different metabotypes characterizing different subjects and relating to individual response to treatment.Conclusion
A 12-resonance metabolic signature of GDN at the time of diagnosis was identified and the evaluation of the impact of insulin and/or diet therapies enabled responsive/resistant metabolic pathways and treatment side-effects to be identified.11.
Hailong Zhang Longzhen Cui Wen Liu Zhenfeng Wang Yang Ye Xue Li Huijuan Wang 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):47
Introduction
Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.Objectives
We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.Methods
1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).Results
There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.Conclusion
To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.12.
13.
Sandra Castillo Dorothee Barth Mikko Arvas Tiina M. Pakula Esa Pitkänen Peter Blomberg Tuulikki Seppanen-Laakso Heli Nygren Dhinakaran Sivasiddarthan Merja Penttilä Merja Oja 《Biotechnology for biofuels》2016,9(1):252
Background
Trichoderma reesei is one of the main sources of biomass-hydrolyzing enzymes for the biotechnology industry. There is a need for improving its enzyme production efficiency. The use of metabolic modeling for the simulation and prediction of this organism’s metabolism is potentially a valuable tool for improving its capabilities. An accurate metabolic model is needed to perform metabolic modeling analysis.Results
A whole-genome metabolic model of T. reesei has been reconstructed together with metabolic models of 55 related species using the metabolic model reconstruction algorithm CoReCo. The previously published CoReCo method has been improved to obtain better quality models. The main improvements are the creation of a unified database of reactions and compounds and the use of reaction directions as constraints in the gap-filling step of the algorithm. In addition, the biomass composition of T. reesei has been measured experimentally to build and include a specific biomass equation in the model.Conclusions
The improvements presented in this work on the CoReCo pipeline for metabolic model reconstruction resulted in higher-quality metabolic models compared with previous versions. A metabolic model of T. reesei has been created and is publicly available in the BIOMODELS database. The model contains a biomass equation, reaction boundaries and uptake/export reactions which make it ready for simulation. To validate the model, we dem1onstrate that the model is able to predict biomass production accurately and no stoichiometrically infeasible yields are detected. The new T. reesei model is ready to be used for simulations of protein production processes.14.
Background
Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic reactions suggests a potential way to discover drug targets. 相似文献15.
Farhana R. Pinu Ninna Granucci James Daniell Ting-Li Han Sonia Carneiro Isabel Rocha Jens Nielsen Silas G. Villas-Boas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):43
Introduction
Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies.Materials and Methods
The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow.Conclusions
Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering.16.
Background
Genome-scale metabolic models provide an opportunity for rational approaches to studies of the different reactions taking place inside the cell. The integration of these models with gene regulatory networks is a hot topic in systems biology. The methods developed to date focus mostly on resolving the metabolic elements and use fairly straightforward approaches to assess the impact of genome expression on the metabolic phenotype.Results
We present here a method for integrating the reverse engineering of gene regulatory networks into these metabolic models. We applied our method to a high-dimensional gene expression data set to infer a background gene regulatory network. We then compared the resulting phenotype simulations with those obtained by other relevant methods.Conclusions
Our method outperformed the other approaches tested and was more robust to noise. We also illustrate the utility of this method for studies of a complex biological phenomenon, the diauxic shift in yeast.17.
Zinandré Stander Laneke Luies Lodewyk J. Mienie Karen M. Keane Glyn Howatson Tom Clifford Emma J. Stevenson Du Toit Loots 《Metabolomics : Official journal of the Metabolomic Society》2018,14(11):150
Introduction
Endurance races have been associated with a substantial amount of adverse effects which could lead to chronic disease and long-term performance impairment. However, little is known about the holistic metabolic changes occurring within the serum metabolome of athletes after the completion of a marathon.Objectives
Considering this, the aim of this study was to better characterize the acute metabolic changes induced by a marathon.Methods
Using an untargeted two dimensional gas chromatography time-of-flight mass spectrometry metabolomics approach, pre- and post-marathon serum samples of 31 athletes were analyzed and compared to identify those metabolites varying the most after the marathon perturbation.Results
Principle component analysis of the comparative groups indicated natural differentiation due to variation in the total metabolite profiles. Elevated concentrations of carbohydrates, fatty acids, tricarboxylic acid cycle intermediates, ketones and reduced concentrations of amino acids indicated a metabolic shift between various fuel substrate systems. Additionally, elevated odd-chain fatty acids and α-hydroxy acids indicated the utilization of α-oxidation and autophagy as alternative energy-producing mechanisms. Adaptations in gut microbe-associated markers were also observed and correlated with the metabolic flexibility of the athlete.Conclusion
From these results it is evident that a marathon places immense strain on the energy-producing pathways of the athlete, leading to extensive protein degradation, oxidative stress, mammalian target of rapamycin complex 1 inhibition and autophagy. A better understanding of this metabolic shift could provide new insights for optimizing athletic performance, developing more efficient nutrition regimens and identify strategies to improve recovery.18.
Background
Genome reduction is a common evolutionary process affecting bacterial lineages that establish symbiotic or pathogenic associations with eukaryotic hosts. Such associations yield highly reduced genomes with greatly streamlined metabolic abilities shaped by the type of ecological association with the host. Sodalis glossinidius, the secondary endosymbiont of tsetse flies, represents one of the few complete genomes available of a bacterium at the initial stages of this process. In the present study, genome reduction is studied from a systems biology perspective through the reconstruction and functional analysis of genome-scale metabolic networks of S. glossinidius.Results
The functional profile of ancestral and extant metabolic networks sheds light on the evolutionary events underlying transition to a host-dependent lifestyle. Meanwhile, reductive evolution simulations on the extant metabolic network can predict possible future evolution of S. glossinidius in the context of genome reduction. Finally, knockout simulations in different metabolic systems reveal a gradual decrease in network robustness to different mutational events for bacterial endosymbionts at different stages of the symbiotic association.Conclusions
Stoichiometric analysis reveals few gene inactivation events whose effects on the functionality of S. glossinidius metabolic systems are drastic enough to account for the ecological transition from a free-living to host-dependent lifestyle. The decrease in network robustness across different metabolic systems may be associated with the progressive integration in the more stable environment provided by the insect host. Finally, reductive evolution simulations reveal the strong influence that external conditions exert on the evolvability of metabolic systems. 相似文献19.
Schiff M Benoist JF Aïssaoui S Boespflug-Tanguy O Boepsflug-Tanguy O Mouren MC de Baulny HO Delorme R 《PloS one》2011,6(7):e21932
Background
In the investigation of autism spectrum disorders (ASD), a genetic cause is found in approximately 10–20%. Among these cases, the prevalence of the rare inherited metabolic disorders (IMD) is unknown and poorly evaluated. An IMD responsible for ASD is usually identified by the associated clinical phenotype such as dysmorphic features, ataxia, microcephaly, epilepsy, and severe intellectual disability (ID). In rare cases, however, ASD may be considered as nonsyndromic at the onset of a related IMD.Objectives
To evaluate the utility of routine metabolic investigations in nonsyndromic ASD.Patients and Methods
We retrospectively analyzed the results of a metabolic workup (urinary mucopolysaccharides, urinary purines and pyrimidines, urinary creatine and guanidinoacetate, urinary organic acids, plasma and urinary amino acids) routinely performed in 274 nonsyndromic ASD children.Results
The metabolic parameters were in the normal range for all but 2 patients: one with unspecific creatine urinary excretion and the other with persistent 3-methylglutaconic aciduria.Conclusions
These data provide the largest ever reported cohort of ASD patients for whom a systematic metabolic workup has been performed; they suggest that such a routine metabolic screening does not contribute to the causative diagnosis of nonsyndromic ASD. They also emphasize that the prevalence of screened IMD in nonsyndromic ASD is probably not higher than in the general population (<0.5%). A careful clinical evaluation is probably more reasonable and of better medical practice than a costly systematic workup. 相似文献20.
Ildefonso M. De la Fuente Fernando Vadillo Alberto Luís Pérez-Samartín Martín-Blas Pérez-Pinilla Joseba Bidaurrazaga Antonio Vera-López 《PloS one》2010,5(3)