Literature DB >> 24828982

Use of solid-phase microextraction coupled to gas chromatography-mass spectrometry for determination of urinary volatile organic compounds in autistic children compared with healthy controls.

Rosaria Cozzolino1, Laura De Magistris, Paola Saggese, Matteo Stocchero, Antonella Martignetti, Michele Di Stasio, Antonio Malorni, Rosa Marotta, Floriana Boscaino, Livia Malorni.   

Abstract

Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders which have a severe life-long effect on behavior and social functioning, and which are associated with metabolic abnormalities. Their diagnosis is on the basis of behavioral and developmental signs usually detected before three years of age, and there is no reliable biological marker. The objective of this study was to establish the volatile urinary metabolomic profiles of 24 autistic children and 21 healthy children (control group) to investigate volatile organic compounds (VOCs) as potential biomarkers for ASDs. Solid-phase microextraction (SPME) using DVB/CAR/PDMS sorbent coupled with gas chromatography-mass spectrometry was used to obtain the metabolomic information patterns. Urine samples were analyzed under both acid and alkaline pH, to profile a range of urinary components with different physicochemical properties. Multivariate statistics techniques were applied to bioanalytical data to visualize clusters of cases and to detect the VOCs able to differentiate autistic patients from healthy children. In particular, orthogonal projections to latent structures discriminant analysis (OPLS-DA) achieved very good separation between autistic and control groups under both acidic and alkaline pH, identifying discriminating metabolites. Among these, 3-methyl-cyclopentanone, 3-methyl-butanal, 2-methyl-butanal, and hexane under acid conditions, and 2-methyl-pyrazine, 2,3-dimethyl-pyrazine, and isoxazolo under alkaline pH had statistically higher levels in urine samples from autistic children than from the control group. Further investigation with a higher number of patients should be performed to outline the metabolic origins of these variables, define a possible association with ASDs, and verify the usefulness of these variables for early-stage diagnosis.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24828982     DOI: 10.1007/s00216-014-7855-z

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  15 in total

1.  The Brain-Gut-Microbiome Axis: What Role Does It Play in Autism Spectrum Disorder?

Authors:  Ruth Ann Luna; Tor C Savidge; Kent C Williams
Journal:  Curr Dev Disord Rep       Date:  2016-02-26

2.  Global metabolic profiles in a non-human primate model of maternal immune activation: implications for neurodevelopmental disorders.

Authors:  Joseph C Boktor; Mark D Adame; Destanie R Rose; Cynthia M Schumann; Karl D Murray; Melissa D Bauman; Milo Careaga; Sarkis K Mazmanian; Paul Ashwood; Brittany D Needham
Journal:  Mol Psychiatry       Date:  2022-08-26       Impact factor: 13.437

3.  Intestinal Dysbiosis and Yeast Isolation in Stool of Subjects with Autism Spectrum Disorders.

Authors:  Maria Rosaria Iovene; Francesca Bombace; Roberta Maresca; Anna Sapone; Patrizia Iardino; Annarita Picardi; Rosa Marotta; Chiara Schiraldi; Dario Siniscalco; Nicola Serra; Laura de Magistris; Carmela Bravaccio
Journal:  Mycopathologia       Date:  2016-09-21       Impact factor: 2.574

4.  Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder.

Authors:  Brittany D Needham; Mark D Adame; Gloria Serena; Destanie R Rose; Gregory M Preston; Mary C Conrad; A Stewart Campbell; David H Donabedian; Alessio Fasano; Paul Ashwood; Sarkis K Mazmanian
Journal:  Biol Psychiatry       Date:  2020-10-10       Impact factor: 13.382

5.  Method for Accurate Quantitation of Volatile Organic Compounds in Urine Using Point of Collection Internal Standard Addition.

Authors:  David M Chambers; Kasey C Edwards; Eduardo Sanchez; Christopher M Reese; Alai T Fernandez; Benjamin C Blount; Víctor R De Jesús
Journal:  ACS Omega       Date:  2021-05-04

6.  Urinary volatile organic compounds in overweight compared to normal-weight children: results from the Italian I.Family cohort.

Authors:  Rosaria Cozzolino; Beatrice De Giulio; Pasquale Marena; Antonella Martignetti; Kathrin Günther; Fabio Lauria; Paola Russo; Matteo Stocchero; Alfonso Siani
Journal:  Sci Rep       Date:  2017-11-15       Impact factor: 4.379

7.  Metabolome signature of autism in the human prefrontal cortex.

Authors:  Ilia Kurochkin; Ekaterina Khrameeva; Anna Tkachev; Vita Stepanova; Anna Vanyushkina; Elena Stekolshchikova; Qian Li; Dmitry Zubkov; Polina Shichkova; Tobias Halene; Lothar Willmitzer; Patrick Giavalisco; Schahram Akbarian; Philipp Khaitovich
Journal:  Commun Biol       Date:  2019-06-21

Review 8.  Profiles of urine and blood metabolomics in autism spectrum disorders.

Authors:  Narueporn Likhitweerawong; Chanisa Thonusin; Nonglak Boonchooduang; Orawan Louthrenoo; Intawat Nookaew; Nipon Chattipakorn; Siriporn C Chattipakorn
Journal:  Metab Brain Dis       Date:  2021-08-02       Impact factor: 3.655

Review 9.  Perspective Biological Markers for Autism Spectrum Disorders: Advantages of the Use of Receiver Operating Characteristic Curves in Evaluating Marker Sensitivity and Specificity.

Authors:  Provvidenza M Abruzzo; Alessandro Ghezzo; Alessandra Bolotta; Carla Ferreri; Renato Minguzzi; Arianna Vignini; Paola Visconti; Marina Marini
Journal:  Dis Markers       Date:  2015-11-08       Impact factor: 3.434

10.  An Optimization of Liquid-Liquid Extraction of Urinary Volatile and Semi-Volatile Compounds and Its Application for Gas Chromatography-Mass Spectrometry and Proton Nuclear Magnetic Resonance Spectroscopy.

Authors:  Natalia Drabińska; Piotr Młynarz; Ben de Lacy Costello; Peter Jones; Karolina Mielko; Justyna Mielnik; Raj Persad; Norman Mark Ratcliffe
Journal:  Molecules       Date:  2020-08-11       Impact factor: 4.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.