Urinary metabolomics using gas chromatography-mass spectrometry: potential biomarkers for autism spectrum disorder

Using urine FTIR spectra to screen autism spectrum disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder caused by multiple factors, lacking clear biomarkers. Diagnosing ASD still relies on behavioural and developmental signs and usually requires lengthy observation periods, all of which are demanding for both clinicians and parents. Although many studies have revealed valuable knowledge in this field, no clearly defined, practical, and widely acceptable diagnostic tool exists. In this study, 26 children with ASD (ASD+), aged 3-5 years, and 26 sex and age-matched controls are studied to investigate the diagnostic potential of the Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The urine FTIR spectrum results show a downward trend in the 3000-2600/cm region for ASD+ children when compared to the typically developing (TD) children of the same age. The average area of this region is 25% less in ASD+ level 3 children, 29% less in ASD+ level 2 children, and 16% less in ASD+ level 1 children compared to that of the TD children. Principal component analysis was applied to the two groups using the entire spectrum window and five peaks were identified for further analysis. The correlation between the peaks and natural urine components is validated by artificial urine solutions. Less-than-normal levels of uric acid, phosphate groups, and ammonium ([Formula: see text]) can be listed as probable causes. This study shows that ATR-FTIR can serve as a practical and non-invasive method to screen ASD using the high-frequency region of the urine spectrum.

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

Colorimetric Signal Readout for the Detection of Volatile Organic Compounds Using a Printable Glass-Based Dielectric Barrier Discharge-Type Helium Plasma Detector

In this paper, we report on a printable glass-based manufacturing method and a new proof-of-concept colorimetric signal readout scheme for a dielectric barrier discharge (DBD)-type helium plasma photoionization detector. The sensor consists of a millimeter-sized glass chamber manufactured using a printable glass suspension. Plasma inside the chip is generated using a custom-built power supply (900 V and 83.6 kHz), and the detector uses ∼5 W of power. Our new detection scheme is based on detecting the change in the color of plasma after the introduction of target gases. The change in color is first captured by a smartphone camera as a video output. The recorded video is then processed and converted to an image light intensity vs retention time plot (gas chromatogram) using three standard color space models (red, green, blue (RGB), hue, saturation, lightness (HSL), and hue, saturation, value (HSV)) with RGB performing the best among the three models. We successfully detected three different categories of volatile organic compounds using our new detection scheme and a 30-m-long gas chromatography column: (1) straight-chain alkanes (n-pentane, n-hexane, n-heptane, n-octane, and n-nonane), (2) aromatics (benzene, toluene, and ethylbenzene), and (3) polar compounds (acetone, ethanol, and dichloromethane). The best limit of detection of 10 ng was achieved for benzene at room temperature. Additionally, the device showed excellent performance for different types of sample mixtures consisting of three and five compounds. Our new detector readout method combined with our ability to print complex glass structures provides a new research avenue to analyze complex gas mixtures and their components.

Association of gut microbiota, plasma and fecal metabolite profiles with intellectual development in school-age children

Background

Little is known about how the gut microbiota and metabolic profiles are related to cognitive outcomes in young children until now. It was hypothesized that the gut microbiota, the plasma and fecal metabolites significantly correlated with intelligence quotient (IQ) in school-age children in current study.

Methods

This cross-sectional study enrolled 452 children aged 6-9 years old. IQ was measured using the Wechsler Intelligence Scale for Children-Fourth Edition. Fecal microbiota, plasma and fecal metabolites were analyzed using 16S rRNA amplicon sequencing and targeted metabolomic technologies, respectively.

Results

Restricted maximum likelihood (REML) analyses showed that microbiota composition and fecal metabolites were associated with neither subscale nor full-scale IQ (P: 0.059-0.500). However, plasma metabolites were significantly correlated with the processing speed (P=0.008). In multiple regression analysis after adjusting for confounders and multiple test correction, benzoic acid, azelaic acid, adipic acid, suberic acid and malonic acid selected by the multivariate methods with unbiased variable selection were positively associated with processing speed index (PSI) [Pfalse discovery rate (FDR): 0.006-0.024], whereas pyruvic acid was negatively associated with the PSI and full-scale IQ (PFDR: 0.014-0.030).

Conclusions

In normal school-age children, certain plasma metabolites concentrations but not the gut microbiota composition nor fecal metabolites are correlated with intelligence.

Developmental pyrethroid exposure causes a neurodevelopmental disorder phenotype in mice

Neurodevelopmental disorders (NDDs) are a widespread and growing public health challenge, affecting as many as 17% of children in the United States. Recent epidemiological studies have implicated ambient exposure to pyrethroid pesticides during pregnancy in the risk for NDDs in the unborn child. Using a litter-based, independent discovery-replication cohort design, we exposed mouse dams orally during pregnancy and lactation to the Environmental Protection Agency's reference pyrethroid, deltamethrin, at 3 mg/kg, a concentration well below the benchmark dose used for regulatory guidance. The resulting offspring were tested using behavioral and molecular methods targeting behavioral phenotypes relevant to autism and NDD, as well as changes to the striatal dopamine system. Low-dose developmental exposure to the pyrethroid deltamethrin (DPE) decreased pup vocalizations, increased repetitive behaviors, and impaired both fear conditioning and operant conditioning. Compared with control mice, DPE mice had greater total striatal dopamine, dopamine metabolites, and stimulated dopamine release, but no difference in vesicular dopamine capacity or protein markers of dopamine vesicles. Dopamine transporter protein levels were increased in DPE mice, but not temporal dopamine reuptake. Striatal medium spiny neurons showed changes in electrophysiological properties consistent with a compensatory decrease in neuronal excitability. Combined with previous findings, these results implicate DPE as a direct cause of an NDD-relevant behavioral phenotype and striatal dopamine dysfunction in mice and implicate the cytosolic compartment as the location of excess striatal dopamine.

Untargeted Metabolomic Analysis Reveals the Metabolic Disturbances and Exacerbation of Oxidative Stress in the Cerebral Cortex of a BTBR Mouse Model of Autism

The etiology and pathology of autism spectrum disorders (ASDs) are still poorly understood, which largely limit the treatment and diagnosis of ASDs. Emerging evidence supports that abnormal metabolites in the cerebral cortex of a BTBR mouse model of autism are involved in the pathogenesis of autism. However, systematic study on global metabolites in the cerebral cortex of BTBR mice has not been conducted. The current study aims to characterize metabolic changes in the cerebral cortex of BTBR mice by using an untargeted metabolomic approach based on UPLC-Q-TOF/MS. C57BL/6 J mice were used as a control group. A total of 14 differential metabolites were identified. Compared with the control group, the intensities of PI(16:0/22:5(4Z,7Z,10Z,13Z,16Z)), PC(22:6(4Z,7Z,10Z,13Z,16Z,19Z)/18:1(9Z)), PA(16:0/18:1(11Z)), 17-beta-estradiol-3-glucuronide, and N6,N6,N6-trimethyl-L-lysine decreased significantly (p < 0.01) and the intensities of 2-oxo-4-hydroxy-4-carboxy-5-ureidoimidazoline, LysoPC(20:4(5Z,8Z,11Z,14Z)/0:0), adenosine monophosphate, adenosine-5'-phosphosulfate, LacCer(d18:1/12:0),3-dehydro-L-gulonate, N-(1-deoxy-1-fructosyl)tryptophan, homovanillic acid, and LPA(0:0/18:1(9Z)) increased significantly (p < 0.01) in the BTBR group. These changes in metabolites were closely related to perturbations in lipid metabolism, energy metabolism, purine metabolism, sulfur metabolism, amino acid metabolism, and carnitine biosynthesis. Notably, exacerbation of the oxidative stress response caused by differential prooxidant metabolites led to alteration of antioxidative systems in the cerebral cortex and resulted in mitochondrial dysfunction, further leading to abnormal energy metabolism as an etiological mechanism of autism. A central role of abnormal metabolites in neurological functions associated with behavioral outcomes and disturbance of sulfur metabolism and carnitine biosynthesis were found in the cerebral cortex of BTBR mice, which helped increase our understanding for exploring the pathological mechanism of autism.

The Difference of Gut Microbiota and Their Correlations With Urinary Organic Acids Between Autistic Children With and Without Atopic Dermatitis

Autism is a kind of biologically based neurodevelopmental condition, and the coexistence of atopic dermatitis (AD) is not uncommon. Given that the gut microbiota plays an important role in the development of both diseases, we aimed to explore the differences of gut microbiota and their correlations with urinary organic acids between autistic children with and without AD. We enrolled 61 autistic children including 36 with AD and 25 without AD. The gut microbiota was sequenced by metagenomic shotgun sequencing, and the diversity, compositions, and functional pathways were analyzed further. Urinary organic acids were assayed by gas chromatography–mass spectrometry, and univariate/multivariate analyses were applied. Spearman correlation analysis was conducted to explore their relationships. In our study, AD individuals had more prominent gastrointestinal disorders. The alpha diversity of the gut microbiota was lower in the AD group. LEfSe analysis showed a higher abundance of Anaerostipes caccae, Eubacterium hallii, and Bifidobacterium bifidum in AD individuals, with Akkermansia muciniphila, Roseburia intestinalis, Haemophilus parainfluenzae, and Rothia mucilaginosa in controls. Meanwhile, functional profiles showed that the pathway of lipid metabolism had a higher proportion in the AD group, and the pathway of xenobiotics biodegradation was abundant in controls. Among urinary organic acids, adipic acid, 3-hydroxyglutaric acid, tartaric acid, homovanillic acid, 2-hydroxyphenylacetic acid, aconitic acid, and 2-hydroxyhippuric acid were richer in the AD group. However, only adipic acid remained significant in the multivariate analysis (OR = 1.513, 95% CI [1.042, 2.198], P = 0.030). In the correlation analysis, Roseburia intestinalis had a negative correlation with aconitic acid (r = -0.14, P = 0.02), and the latter was positively correlated with adipic acid (r = 0.41, P = 0.006). Besides, the pathway of xenobiotics biodegradation seems to inversely correlate with adipic acid (r = -0.42, P = 0.18). The gut microbiota plays an important role in the development of AD in autistic children, and more well-designed studies are warranted to explore the underlying mechanism.