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Al-Beltagi M, Saeed NK, Bediwy AS, Elbeltagi R. Metabolomic changes in children with autism. World J Clin Pediatr 2024; 13:92737. [PMID: 38947988 PMCID: PMC11212761 DOI: 10.5409/wjcp.v13.i2.92737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 04/23/2024] [Accepted: 05/06/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and repetitive behaviors. Metabolomic profiling has emerged as a valuable tool for understanding the underlying metabolic dysregulations associated with ASD. AIM To comprehensively explore metabolomic changes in children with ASD, integrating findings from various research articles, reviews, systematic reviews, meta-analyses, case reports, editorials, and a book chapter. METHODS A systematic search was conducted in electronic databases, including PubMed, PubMed Central, Cochrane Library, Embase, Web of Science, CINAHL, Scopus, LISA, and NLM catalog up until January 2024. Inclusion criteria encompassed research articles (83), review articles (145), meta-analyses (6), systematic reviews (6), case reports (2), editorials (2), and a book chapter (1) related to metabolomic changes in children with ASD. Exclusion criteria were applied to ensure the relevance and quality of included studies. RESULTS The systematic review identified specific metabolites and metabolic pathways showing consistent differences in children with ASD compared to typically developing individuals. These metabolic biomarkers may serve as objective measures to support clinical assessments, improve diagnostic accuracy, and inform personalized treatment approaches. Metabolomic profiling also offers insights into the metabolic alterations associated with comorbid conditions commonly observed in individuals with ASD. CONCLUSION Integration of metabolomic changes in children with ASD holds promise for enhancing diagnostic accuracy, guiding personalized treatment approaches, monitoring treatment response, and improving outcomes. Further research is needed to validate findings, establish standardized protocols, and overcome technical challenges in metabolomic analysis. By advancing our understanding of metabolic dysregulations in ASD, clinicians can improve the lives of affected individuals and their families.
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Affiliation(s)
- Mohammed Al-Beltagi
- Department of Pediatric, Faculty of Medicine, Tanta University, Tanta 31511, Alghrabia, Egypt
- Department of Pediatric, University Medical Center, King Abdulla Medical City, Arabian Gulf University, Manama 26671, Bahrain
- Department of Pediatric, University Medical Center, Dr. Sulaiman Al Habib Medical Group, Manama, Bahrain, Manama 26671, Bahrain
| | - Nermin Kamal Saeed
- Medical Microbiology Section, Department of Pathology, Salmaniya Medical Complex, Ministry of Health, Kingdom of Bahrain, Manama 12, Bahrain
- Medical Microbiology Section, Department of Pathology, Irish Royal College of Surgeon, Bahrain, Busaiteen 15503, Muharraq, Bahrain
| | - Adel Salah Bediwy
- Department of Pulmonology, Faculty of Medicine, Tanta University, Tanta 31527, Alghrabia, Egypt
- Department of Chest Disease, University Medical Center, King Abdulla Medical City, Arabian Gulf University, Manama 26671, Bahrain
- Department of Chest Disease, University Medical Center, Dr. Sulaiman Al Habib Medical Group, Manama, Manama 26671, Bahrain
| | - Reem Elbeltagi
- Department of Medicine, The Royal College of Surgeons in Ireland - Bahrain, Busiateen 15503, Muharraq, Bahrain
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Vankwani S, Mirza MR, Awan FR, Zafar M, Nawrocki A, Wasim M, Khan HN, Ayesha H, Larsen MR, Choudhary MI. Label free quantitative proteomic profiling of serum samples of intellectually disabled young patients revealed dysregulation of complement coagulation and cholesterol cascade systems. Metab Brain Dis 2024; 39:855-869. [PMID: 38733546 DOI: 10.1007/s11011-024-01351-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 05/05/2024] [Indexed: 05/13/2024]
Abstract
Intellectual disability is a heterogeneous disorder, diagnosed using intelligence quotient (IQ) score criteria. Currently, no specific clinical test is available to diagnose the disease and its subgroups due to inadequate understanding of the pathophysiology. Therefore, current study was designed to explore the molecular mechanisms involved in disease perturbation, and to identify potential biomarkers for disease diagnosis and prognosis. A total of 250 participants were enrolled in this study, including 200 intellectually disabled (ID) subjects from the subgroups (mild, moderate, and severe) with age and gender matched healthy controls (n = 50). Initially, IQ testing score and biochemical profile of each subject was generated, followed by label-free quantitative proteomics of subgroups of IQ and healthy control group through nano-LC/MS- mass spectrometry. A total of 310 proteins were identified, among them198 proteins were common among all groups. Statistical analysis (ANOVA) of the subgroups of ID showed 142 differentially expressed proteins, in comparison to healthy control group. From these, 120 proteins were found to be common among all subgroups. The remaining 22 proteins were categorized as exclusive proteins found only in disease subgroups. Furthermore, the hierarchical cluster analysis (HCL) of common significant proteins was also performed, followed by PANTHER protein classification and GO functional enrichment analysis. Results provides that the datasets of differentially expressed proteins, belong to the categories of immune / defense proteins, transfer carrier proteins, apolipoproteins, complement proteins, protease inhibitors, hemoglobin proteins etc., they are known to involvein immune system, and complement and coagulation pathway cascade and cholesterol metabolism pathway. Exclusively expressed 22 proteins were found to be disease stage specific and strong PPI network specifically those that have significant role in platelets activation and degranulation, such as Filamin A (FLNA). Furthermore, to validate the mass spectrometric findings, four highly significant proteins (APOA4, SAP, FLNA, and SERPING) were quantified by ELISA in all the study subjects. AUROC analysis showed a significant association of APOA4 (0.830), FLNA (0.958), SAP (0.754) and SERPING (0.600) with the disease. Apolipoprotein A4 (APOA4) has a significant role in cholesterol transport, and in modulation of glucose and lipid metabolism in the CNS. Similarly, FLNA has a crucial role in the nervous system, especially in the functioning of synaptic network. Therefore, both APOA4, and FLNA proteins represent good potential for candidate biomarkers for the diagnosis and prognosis of the intellectual disability. Overall, serum proteome of ID patients provides valuable information of proteins/pathways that are altered during ID progression.
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Affiliation(s)
- Soma Vankwani
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan
| | - Munazza Raza Mirza
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan.
| | - Fazli Rabbi Awan
- Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Jhang Road, P.O. Box. 577, Faisalabad, Pakistan.
| | - Muneeza Zafar
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan
- Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Jhang Road, P.O. Box. 577, Faisalabad, Pakistan
| | - Arkadiusz Nawrocki
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Muhammad Wasim
- Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Jhang Road, P.O. Box. 577, Faisalabad, Pakistan
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Haq Nawaz Khan
- Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Jhang Road, P.O. Box. 577, Faisalabad, Pakistan
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Hina Ayesha
- Department of Pediatrics, Punjab Medical College, Allied & DHQ Hospitals, Faisalabad Medical University, Faisalabad, Pakistan
| | - Martin Rossel Larsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Muhammad Iqbal Choudhary
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan
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3
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Lazar SM, Challman TD, Myers SM. Etiologic Evaluation of Children with Autism Spectrum Disorder. Pediatr Clin North Am 2024; 71:179-197. [PMID: 38423715 DOI: 10.1016/j.pcl.2023.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Autism spectrum disorder (ASD) is clinically and etiologically heterogeneous. A causal genetic variant can be identified in approximately 20% to 25% of affected individuals with current clinical genetic testing, and all patients with an ASD diagnosis should be offered genetic etiologic evaluation. We suggest that exome sequencing with copy number variant coverage should be the first-line etiologic evaluation for ASD. Neuroimaging, neurophysiologic, metabolic, and other biochemical evaluations can provide insight into the pathophysiology of ASD but should be recommended in the appropriate clinical circumstances.
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Affiliation(s)
- Steven M Lazar
- Section of Pediatric Neurology and Developmental Neuroscience, Meyer Center for Developmental Pediatrics & Autism, Baylor College of Medicine - Texas Children's Hospital, 6701 Fannin Street Suite 1250, Houston, TX 77030, USA.
| | - Thomas D Challman
- Geisinger Autism & Developmental Medicine Institute, Geisinger Commonwealth School of Medicine, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, USA
| | - Scott M Myers
- Geisinger Autism & Developmental Medicine Institute, Geisinger Commonwealth School of Medicine, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, USA
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4
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Huang ZY, Lyu ZP, Li HG, You HZ, Yang XN, Cha CH. Des-Arg(9) bradykinin as a causal metabolite for autism spectrum disorder. World J Psychiatry 2024; 14:88-101. [PMID: 38327885 PMCID: PMC10845217 DOI: 10.5498/wjp.v14.i1.88] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/08/2023] [Accepted: 12/07/2023] [Indexed: 01/19/2024] Open
Abstract
BACKGROUND Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder (ASD). However, the etiology of ASD is not completely understood. The presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for ASD. AIM To estimate and interpret the causal relationship between ASD and metabolite profile, taking into consideration both genetic and environmental influences. METHODS A two-sample Mendelian randomization (MR) analysis was conducted using summarized data from large-scale genome-wide association studies (GWAS) including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy controls. Metabolites in plasma were set as exposures with ASD as the main outcome. The causal relationships were estimated using the inverse variant weight (IVW) algorithm. We also performed leave-one-out sensitivity tests to validate the robustness of the results. Based on the drafted metabolites, enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome, SwissTargetPrediction, STRING, and Metascape. RESULTS Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD (β = 0.262, SE = 0.064, PIVW = 4.64 × 10-5). The association was robust, with no significant heterogeneity among instrument variables (PMR Egger = 0.663, PIVW = 0.906) and no evidence of pleiotropy (P = 0.949). Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9) bradykinin and ASD. CONCLUSION Through the application of MR, this study provides practical insights into the potential causal association between plasma metabolites and ASD. These findings offer perspectives for the discovery of diagnostic or predictive biomarkers to support clinical practice in treating ASD.
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Affiliation(s)
- Zhong-Yu Huang
- Center for Medical Research on Innovation and Translation, Institute of Clinical Medicine, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou 510000, Guangdong Province, China
| | - Zi-Pan Lyu
- School of Biological Sciences, Nanyang Technological University, Nanyang Ave 639798, Singapore
| | - Hong-Gui Li
- Department of Pediatrics, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China
| | - Hua-Zhi You
- Department of Nutrition, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China
| | - Xiang-Na Yang
- Department of Pediatric Traditional Chinese Medicine Clinic, Guangzhou Women and Children's Medical Center, Guangzhou 510632, Guangdong Province, China
| | - Cai-Hui Cha
- Department of Psychology, Guangzhou Women and Children's Medical Center, Guangzhou 510632, Guangdong Province, China
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5
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Xiao J, Jain A, Bellia G, Nyhan K, Liew Z. A scoping review of multigenerational impacts of grandparental exposures on mental health in grandchildren. Curr Environ Health Rep 2023; 10:369-382. [PMID: 38008881 DOI: 10.1007/s40572-023-00413-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/27/2023] [Indexed: 11/28/2023]
Abstract
PURPOSE OF REVIEW The multigenerational effects of grandparental exposures on their grandchildren's mental health and neurodevelopment are gaining research attention. We conducted a scoping review to summarize the current epidemiological studies investigating pregnancy-related and environmental factors that affected grandparental pregnancies and mental health outcomes in their grandchildren. We also identified methodological challenges that affect these multigenerational health studies and discuss opportunities for future research. RECENT FINDINGS We performed a literature search using PubMed and Embase and included 18 articles for this review. The most investigated grandparental pregnancy-related factors were the grandparental age of pregnancy (N = 6), smoking during pregnancy (N = 4), and medication intake (N = 3). The most frequently examined grandchild outcomes were autism spectrum disorder (N = 6) and attention-deficit/hyperactivity disorder (N = 4). Among these studies, grandparental smoking and the use of diethylstilbestrol were more consistently reported to be associated with neurodevelopmental disorders, while the findings for grandparental age vary across the maternal or paternal line. Grandmaternal weight, adverse delivery outcomes, and other spatial-temporal markers of physical and social environmental stressors require further scrutiny. The current body of literature has suggested that mental and neurodevelopmental disorders may be outcomes of unfavorable exposures originating from the grandparental generation during their pregnancies. To advance the field, we recommend research efforts into setting up multigenerational studies with prospectively collected data that span through at least three generations, incorporating spatial, environmental, and biological markers for exposure assessment, expanding the outcome phenotypes evaluated, and developing a causal analytical framework including mediation analyses specific for multigenerational research.
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Affiliation(s)
- Jingyuan Xiao
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, USA
| | - Anushka Jain
- Department of Social Behavioral Sciences, Yale School of Public Health, New Haven, USA
| | - Giselle Bellia
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, USA
| | - Kate Nyhan
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, USA.
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, USA.
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Sarigul N, Bozatli L, Kurultak I, Korkmaz F. Using urine FTIR spectra to screen autism spectrum disorder. Sci Rep 2023; 13:19466. [PMID: 37945643 PMCID: PMC10636094 DOI: 10.1038/s41598-023-46507-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023] Open
Abstract
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.
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Affiliation(s)
- Neslihan Sarigul
- Institute of Nuclear Science, Hacettepe University, Ankara, Turkey.
| | - Leyla Bozatli
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Trakya University, Edirne, Turkey
| | - Ilhan Kurultak
- Department of Nephrology, Faculty of Medicine, Trakya University, Edirne, Turkey
| | - Filiz Korkmaz
- Biophysics Laboratory, Faculty of Engineering, Atilim University, Ankara, Turkey
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Kaupper CS, Blaauwendraad SM, Cecil CAM, Mulder RH, Gaillard R, Goncalves R, Borggraefe I, Koletzko B, Jaddoe VWV. Cord Blood Metabolite Profiles and Their Association with Autistic Traits in Childhood. Metabolites 2023; 13:1140. [PMID: 37999236 PMCID: PMC10672851 DOI: 10.3390/metabo13111140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/02/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023] Open
Abstract
Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental condition. Gene-environmental interactions in early stages of life might alter metabolic pathways, possibly contributing to ASD pathophysiology. Metabolomics may serve as a tool to identify underlying metabolic mechanisms contributing to ASD phenotype and could help to unravel its complex etiology. In a population-based, prospective cohort study among 783 mother-child pairs, cord blood serum concentrations of amino acids, non-esterified fatty acids, phospholipids, and carnitines were obtained using liquid chromatography coupled with tandem mass spectrometry. Autistic traits were measured at the children's ages of 6 (n = 716) and 13 (n = 648) years using the parent-reported Social Responsiveness Scale. Lower cord blood concentrations of SM.C.39.2 and NEFA16:1/16:0 were associated with higher autistic traits among 6-year-old children, adjusted for sex and age at outcome. After more stringent adjustment for confounders, no significant associations of cord blood metabolites and autistic traits at ages 6 and 13 were detected. Differences in lipid metabolism (SM and NEFA) might be involved in ASD-related pathways and are worth further investigation.
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Affiliation(s)
- Christin S. Kaupper
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Sophia M. Blaauwendraad
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Charlotte A. M. Cecil
- Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, 3000 CA Rotterdam, The Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
| | - Rosa H. Mulder
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Romy Gaillard
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Romy Goncalves
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Ingo Borggraefe
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Comprehensive Epilepsy Center for Children and Adolescents, Dr. von Hauner Children’s Hospital, LMU University Hospitals, LMU—Ludwig-Maximilians Universität, 80337 Munich, Germany
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children’s Hospital, LMU University Hospitals, LMU—Ludwig-Maximilians Universität, 80337 Munich, Germany
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands (R.G.)
- Department of Pediatrics, Sophia’s Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
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8
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Smith AM, Donley ELR, Ney DM, Amaral DG, Burrier RE, Natowicz MR. Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics. Front Psychiatry 2023; 14:1249578. [PMID: 37928922 PMCID: PMC10622772 DOI: 10.3389/fpsyt.2023.1249578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/30/2023] [Indexed: 11/07/2023] Open
Abstract
Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.
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Affiliation(s)
- Alan M. Smith
- Stemina Biomarker Discovery, Inc, Madison, WI, United States
| | | | - Denise M. Ney
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, The MIND Institute, University of California, Davis, Davis, CA, United States
| | | | - Marvin R. Natowicz
- Pathology and Laboratory Medicine, Genomic Medicine, Neurological and Pediatrics Institutes, Cleveland Clinic, Cleveland, OH, United States
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Siracusano M, Arturi L, Riccioni A, Noto A, Mussap M, Mazzone L. Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder. Int J Mol Sci 2023; 24:13404. [PMID: 37686207 PMCID: PMC10487559 DOI: 10.3390/ijms241713404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/09/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
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.
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Affiliation(s)
- Martina Siracusano
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
- Child Neurology and Psychiatry Unit, Department of Neurosciences, Policlinico Tor Vergata Hospital, Viale Oxford 81, 00133 Rome, Italy; (L.A.); (A.R.); (L.M.)
| | - Lucrezia Arturi
- Child Neurology and Psychiatry Unit, Department of Neurosciences, Policlinico Tor Vergata Hospital, Viale Oxford 81, 00133 Rome, Italy; (L.A.); (A.R.); (L.M.)
| | - Assia Riccioni
- Child Neurology and Psychiatry Unit, Department of Neurosciences, Policlinico Tor Vergata Hospital, Viale Oxford 81, 00133 Rome, Italy; (L.A.); (A.R.); (L.M.)
| | - Antonio Noto
- Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria, SS 554, Km 4.5, 09042 Monserrato, Italy
| | - Michele Mussap
- Department of Surgical Sciences, School of Medicine, University of Cagliari, Cittadella Universitaria, SS 554, Km 4.5, 09042 Monserrato, Italy
| | - Luigi Mazzone
- Child Neurology and Psychiatry Unit, Department of Neurosciences, Policlinico Tor Vergata Hospital, Viale Oxford 81, 00133 Rome, Italy; (L.A.); (A.R.); (L.M.)
- Systems Medicine Department, University of Rome Tor Vergata, Montpellier Street 1, 00133 Rome, Italy
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10
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Sotelo-Orozco J, Schmidt RJ, Slupsky CM, Hertz-Picciotto I. Investigating the Urinary Metabolome in the First Year of Life and Its Association with Later Diagnosis of Autism Spectrum Disorder or Non-Typical Neurodevelopment in the MARBLES Study. Int J Mol Sci 2023; 24:9454. [PMID: 37298406 PMCID: PMC10254021 DOI: 10.3390/ijms24119454] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
Developmental disabilities are often associated with alterations in metabolism. However, it remains unknown how early these metabolic issues may arise. This study included a subset of children from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) prospective cohort study. In this analysis, 109 urine samples collected at 3, 6, and/or 12 months of age from 70 children with a family history of ASD who went on to develop autism spectrum disorder (ASD n = 17), non-typical development (Non-TD n = 11), or typical development (TD n = 42) were investigated by nuclear magnetic resonance (NMR) spectroscopy to measure urinary metabolites. Multivariate principal component analysis and a generalized estimating equation were performed with the objective of exploring the associations between urinary metabolite levels in the first year of life and later adverse neurodevelopment. We found that children who were later diagnosed with ASD tended to have decreased urinary dimethylamine, guanidoacetate, hippurate, and serine, while children who were later diagnosed with Non-TD tended to have elevated urinary ethanolamine and hypoxanthine but lower methionine and homovanillate. Children later diagnosed with ASD or Non-TD both tended to have decreased urinary 3-aminoisobutyrate. Our results suggest subtle alterations in one-carbon metabolism, gut-microbial co-metabolism, and neurotransmitter precursors observed in the first year of life may be associated with later adverse neurodevelopment.
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Affiliation(s)
- Jennie Sotelo-Orozco
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA 95616, USA; (R.J.S.); (I.H.-P.)
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA 95616, USA; (R.J.S.); (I.H.-P.)
- Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, School of Medicine, University of California Davis, Sacramento, CA 95817, USA
| | - Carolyn M. Slupsky
- Department of Nutrition, University of California, Davis, CA 95616, USA;
- Department of Food Science and Technology, University of California, Davis, CA 95616, USA
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA 95616, USA; (R.J.S.); (I.H.-P.)
- Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, School of Medicine, University of California Davis, Sacramento, CA 95817, USA
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11
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Senarathne UD, Indika NLR, Jezela-Stanek A, Ciara E, Frye RE, Chen C, Stepien KM. Biochemical, Genetic and Clinical Diagnostic Approaches to Autism-Associated Inherited Metabolic Disorders. Genes (Basel) 2023; 14:genes14040803. [PMID: 37107561 PMCID: PMC10138025 DOI: 10.3390/genes14040803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/22/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders characterized by impaired social interaction, limited communication skills, and restrictive and repetitive behaviours. The pathophysiology of ASD is multifactorial and includes genetic, epigenetic, and environmental factors, whereas a causal relationship has been described between ASD and inherited metabolic disorders (IMDs). This review describes biochemical, genetic, and clinical approaches to investigating IMDs associated with ASD. The biochemical work-up includes body fluid analysis to confirm general metabolic and/or lysosomal storage diseases, while the advances and applications of genomic testing technology would assist with identifying molecular defects. An IMD is considered likely underlying pathophysiology in ASD patients with suggestive clinical symptoms and multiorgan involvement, of which early recognition and treatment increase their likelihood of achieving optimal care and a better quality of life.
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Affiliation(s)
- Udara D. Senarathne
- Department of Biochemistry, Faculty of Medical Sciences, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka
- Department of Chemical Pathology, Monash Health Pathology, Monash Health, Melbourne, VIC 3168, Australia
| | - Neluwa-Liyanage R. Indika
- Department of Biochemistry, Faculty of Medical Sciences, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka
| | - Aleksandra Jezela-Stanek
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Elżbieta Ciara
- Department of Medical Genetics, The Children’s Memorial Health Institute, 04-730 Warsaw, Poland
| | - Richard E. Frye
- Autism Discovery and Treatment Foundation, Phoenix, AZ 85050, USA
| | - Cliff Chen
- Clinical Neuropsychology Department, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
| | - Karolina M. Stepien
- Adult Inherited Metabolic Diseases, Mark Holland Unit, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK
- Division of Diabetes, Endocrinology and Gastroenterology, University of Manchester, Manchester M13 9PL, UK
- Correspondence:
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12
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Costello SM, Cheney AM, Waldum A, Tripet B, Cotrina-Vidal M, Kaufmann H, Norcliffe-Kaufmann L, Lefcort F, Copié V. A Comprehensive NMR Analysis of Serum and Fecal Metabolites in Familial Dysautonomia Patients Reveals Significant Metabolic Perturbations. Metabolites 2023; 13:metabo13030433. [PMID: 36984872 PMCID: PMC10057143 DOI: 10.3390/metabo13030433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/06/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023] Open
Abstract
Central metabolism has a profound impact on the clinical phenotypes and penetrance of neurological diseases such as Alzheimer’s (AD) and Parkinson’s (PD) diseases, Amyotrophic Lateral Sclerosis (ALS) and Autism Spectrum Disorder (ASD). In contrast to the multifactorial origin of these neurological diseases, neurodevelopmental impairment and neurodegeneration in Familial Dysautonomia (FD) results from a single point mutation in the ELP1 gene. FD patients represent a well-defined population who can help us better understand the cellular networks underlying neurodegeneration, and how disease traits are affected by metabolic dysfunction, which in turn may contribute to dysregulation of the gut–brain axis of FD. Here, 1H NMR spectroscopy was employed to characterize the serum and fecal metabolomes of FD patients, and to assess similarities and differences in the polar metabolite profiles between FD patients and healthy relative controls. Findings from this work revealed noteworthy metabolic alterations reflected in energy (ATP) production, mitochondrial function, amino acid and nucleotide catabolism, neurosignaling molecules, and gut-microbial metabolism. These results provide further evidence for a close interconnection between metabolism, neurodegeneration, and gut microbiome dysbiosis in FD, and create an opportunity to explore whether metabolic interventions targeting the gut–brain–metabolism axis of FD could be used to redress or slow down the progressive neurodegeneration observed in FD patients.
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Affiliation(s)
- Stephanann M. Costello
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
| | - Alexandra M. Cheney
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
| | - Annie Waldum
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
| | - Brian Tripet
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
| | - Maria Cotrina-Vidal
- Department of Neurology, New York University School of Medicine, New York, NY 10017, USA
| | - Horacio Kaufmann
- Department of Neurology, New York University School of Medicine, New York, NY 10017, USA
| | | | - Frances Lefcort
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, MT 59717, USA
| | - Valérie Copié
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
- Correspondence: ; Tel.: +1-406-994-7244
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13
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Hampel H, Gao P, Cummings J, Toschi N, Thompson PM, Hu Y, Cho M, Vergallo A. The foundation and architecture of precision medicine in neurology and psychiatry. Trends Neurosci 2023; 46:176-198. [PMID: 36642626 PMCID: PMC10720395 DOI: 10.1016/j.tins.2022.12.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/18/2022] [Accepted: 12/14/2022] [Indexed: 01/15/2023]
Abstract
Neurological and psychiatric diseases have high degrees of genetic and pathophysiological heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have focused on late-stage syndromic aspects of these diseases, with little consideration of the underlying biology. Advances in disease modeling and methodological design have paved the way for the development of precision medicine (PM), an established concept in oncology with growing attention from other medical specialties. We propose a PM architecture for central nervous system diseases built on four converging pillars: multimodal biomarkers, systems medicine, digital health technologies, and data science. We discuss Alzheimer's disease (AD), an area of significant unmet medical need, as a case-in-point for the proposed framework. AD can be seen as one of the most advanced PM-oriented disease models and as a compelling catalyzer towards PM-oriented neuroscience drug development and advanced healthcare practice.
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Affiliation(s)
- Harald Hampel
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Peng Gao
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy; Athinoula A. Martinos Center for Biomedical Imaging and Harvard Medical School, Boston, MA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yan Hu
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Min Cho
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Andrea Vergallo
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
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14
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Moravej H, Inaloo S, Nahid S, Mazloumi S, Nemati H, Moosavian T, Nasiri J, Ghasemi F, Alaei MR, Dalili S, Aminzadeh M, Katibeh P, Amirhakimi A, Yazdani N, Ilkhanipoor H, Afshar Z, Hadipour F, Hadipour Z. Inborn Errors of Metabolism Associated With Autism Among Children: A Multicenter Study from Iran. Indian Pediatr 2023. [PMID: 36604934 DOI: 10.1007/s13312-023-2833-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
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15
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Siani-Rose M, Cox S, Goldstein B, Abrams D, Taylor M, Kurek I. Cannabis-Responsive Biomarkers: A Pharmacometabolomics-Based Application to Evaluate the Impact of Medical Cannabis Treatment on Children with Autism Spectrum Disorder. Cannabis Cannabinoid Res 2023; 8:126-137. [PMID: 34874191 PMCID: PMC9940806 DOI: 10.1089/can.2021.0129] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Introduction: Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions that impact behavior, communication, social interaction, and learning abilities. Treatment of ASD with medical cannabis (MC) shows promising results in reducing the severity of certain behavioral aspects. The goals of this observational study are to demonstrate the potential of metabolic biomarkers to (1) objectively determine the impact on metabolites of MC treatment and (2) suggest the metabolic pathways of children with ASD, who respond to MC treatment. Materials and Methods: The impact of effective physician-supervised MC treatment on children with ASD (n=15), compared with an age-matched group of typically developing (TD; n=9) children, was evaluated in an observational study design. Each child followed a unique MC regimen determined by their specific response over at least 1 year of treatment, which included the following: tetrahydrocannabinol-dominant MC (dosing range 0.05-50 mg per dose) in 40% of children and cannabidiol-dominant MC (dosing range 7.5-200 mg per dose) in 60% of children. Samples from the ASD group collected pre-MC treatment and at time of maximal impact, and from the TD group, were subjected to salivary metabolomics analysis. Ten minutes before saliva sampling, parents filled out behavioral rating surveys. Results: Sixty-five potential cannabis-responsive biomarkers exhibiting a shift toward the TD physiological levels were identified in children with ASD after MC treatment. For each biomarker, the physiological levels were determined based on the values detected in the TD group. A similar qualitative improvement trend in children with ASD treated with MC was also observed in the behavioral surveys. Twenty-three potential Cannabis-Responsive biomarkers exhibiting change toward TD mean were categorized as anti-inflammatory, bioenergy associated, neurotransmitters, amino acids, and endocannabinoids. The changes in the levels of the Cannabis-Responsive biomarkers N-acetylaspartic acid, spermine, and dehydroisoandrosterone 3-sulfate have been previously linked to behavioral symptoms commonly observed in individuals with ASD. Conclusions: Our results suggest Cannabis-Responsive biomarkers shift toward the TD mean after MC treatment and can potentially quantify benefit at the metabolic level. These changes appear to be similar to the trend described in behavior surveys. Larger trials are needed to confirm these preliminary findings.
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Affiliation(s)
| | - Stephany Cox
- Cannformatics, Inc., San Francisco, California, USA
| | | | | | | | - Itzhak Kurek
- Cannformatics, Inc., San Francisco, California, USA
- Address correspondence to: Itzhak Kurek, PhD Cannformatics, Inc., 3869 Cesar Chavez Street, San Francisco, CA 94131, USA,
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16
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Gagliano A, Murgia F, Capodiferro AM, Tanca MG, Hendren A, Falqui SG, Aresti M, Comini M, Carucci S, Cocco E, Lorefice L, Roccella M, Vetri L, Sotgiu S, Zuddas A, Atzori L. 1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome. J Clin Med 2022; 11:6493. [PMID: 36362721 PMCID: PMC9658067 DOI: 10.3390/jcm11216493] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 10/24/2022] [Accepted: 10/27/2022] [Indexed: 11/03/2023] Open
Abstract
We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers.
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Affiliation(s)
- Antonella Gagliano
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
- Department of Health Science, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
| | - Federica Murgia
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, 09042 Cagliari, Italy
| | - Agata Maria Capodiferro
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Marcello Giuseppe Tanca
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Aran Hendren
- Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Stella Giulia Falqui
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Michela Aresti
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Martina Comini
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Sara Carucci
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Eleonora Cocco
- Multiple Sclerosis Regional Center, ASSL Cagliari, Department of Medical Sciences and Public Health, University of Cagliari, 09126 Cagliari, Italy
| | - Lorena Lorefice
- Multiple Sclerosis Regional Center, ASSL Cagliari, 09126 Cagliari, Italy
| | - Michele Roccella
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy
| | - Luigi Vetri
- Oasi Research Institute-IRCCS, Via Conte Ruggero 73, 94018 Troina, Italy
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medicine, Surgery and Farmacy, University of Sassari, 07100 Sassari, Italy
| | - Alessandro Zuddas
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Luigi Atzori
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, 09042 Cagliari, Italy
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17
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Daneberga Z, Nakazawa-Miklasevica M, Berga-Svitina E, Murmane D, Isarova D, Cupane L, Masinska M, Nartisa I, Lazdane A, Miklasevics E. Urinary organic acids spectra in children with altered gut microbiota composition and autistic spectrum disorder. Nord J Psychiatry 2022; 76:523-529. [PMID: 34935590 DOI: 10.1080/08039488.2021.2014954] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Introduction: Alteration of human gut microbiota is described in a number of neuro-developmental and cognitive disorders including autistic spectrum disorder (ASD). Along with the changes in the gut microbiota, children with ASD are also reported to have changes in urinary organic acid spectra implying these metabolites as potential biomarkers for gastrointestinal dysbiosis.Aim: Identify urinary metabolites that would indicate specific changes in the gut microbiota and could be useful as biomarkers.Methods: The study group consisted of 44 children with ASD. Urinary organic acids spectra and composition of gut microbiota were analysed.Results: Any significant deviation in quantified metabolites compared to the reference values were not confirmed. The main variations were detected in concentration of p-cresol and 3-(3-hydroxyphenyl)-3-hydroxypropionic acid (HPHPA), but we cannot confirm the presence of HPHPA in urine as a biomarker for Clostridium sp. overgrowth in the gut. The acquired results indicate higher relative abundance of Firmicutes phylum alone may be attributed to increased concentration of p-cresol in urine. Decreased Bacteroidetes/Firmicutes ratio was found in the group with the presence of HPHPA in urine.Conclusions: Metabolites of human urine can be used as biomarkers for alterations of gut microbiota with caution, guided treatment should be administrated only based on gut microbiota analysis results or in combination with urinary organic acid results, but not solely based on organic acid biomarkers.
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Affiliation(s)
- Zanda Daneberga
- Institute of Oncology, Riga Stradins University, Riga, Latvia.,Laboratory, Children's Clinical University Hospital, Riga, Latvia
| | | | | | - Daiga Murmane
- Clinic of Medical Genetics and Prenatal Diagnosis, Children's Clinical University Hospital, Riga, Latvia
| | - Dana Isarova
- Infection Prevention and Control Department, Children's Clinical University Hospital, Riga, Latvia
| | - Liene Cupane
- Clinic of General Paediatrics, Children's Clinical University Hospital, Riga, Latvia.,Department of Paediatrics, Riga Stradins University, Riga, Latvia
| | - Madara Masinska
- Clinic of Medical Genetics and Prenatal Diagnosis, Children's Clinical University Hospital, Riga, Latvia
| | - Inga Nartisa
- Laboratory, Children's Clinical University Hospital, Riga, Latvia
| | - Andzela Lazdane
- Laboratory, Children's Clinical University Hospital, Riga, Latvia
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18
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NMR-Based Metabolomics of Rat Hippocampus, Serum, and Urine in Two Models of Autism. Mol Neurobiol 2022; 59:5452-5475. [PMID: 35715683 DOI: 10.1007/s12035-022-02912-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 06/03/2022] [Indexed: 10/18/2022]
Abstract
Autism spectrum disorders (ASDs) are increasingly diagnosed as developmental disabilities of unclear etiology related to genetic, epigenetic, or environmental factors. The diagnosis of ASD in children is based on the recognition of typical behavioral symptoms, while no reliable biomarkers are available. Rats in whom ASD-like symptoms are due to maternal administration of the teratogenic drugs valproate or thalidomide on critical day 11 of pregnancy are widely used models in autism research. The present studies, aimed at detecting changes in the levels of hydrophilic and hydrophobic metabolites, were carried out on 1-month-old rats belonging to the abovementioned two ASD models and on a control group. Analysis of both hydrophilic and hydrophobic metabolite levels gives a broader view of possible mechanisms involved in the pathogenesis of autism. Hippocampal proton magnetic resonance (MRS) spectroscopy and ex vivo nuclear magnetic resonance (NMR) analysis of serum and urine samples were used. The results were analyzed using advanced statistical tests. Both the results of our present MRS studies of the hippocampus and of the NMR studies of body fluids in both ASD models, particularly from the THAL model, appeared to be consistent with previously published NMR results of hippocampal homogenates and data from the literature on autistic children. We detected symptoms of disturbances in neurotransmitter metabolism, energy deficit, and oxidative stress, as well as intestinal malfunction, which shed light on the pathogenesis of ASD and could be used for diagnostic purposes. These results confirm the usefulness of the noninvasive techniques used in ASD studies.
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19
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Tian X, Liu X, Wang Y, Liu Y, Ma J, Sun H, Li J, Tang X, Guo Z, Sun W, Zhang J, Song W. Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD). Front Psychiatry 2022; 13:819498. [PMID: 35669266 PMCID: PMC9163378 DOI: 10.3389/fpsyt.2022.819498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 04/19/2022] [Indexed: 11/30/2022] Open
Abstract
Objectives Knowledge of the urinary metabolomic profiles of healthy children and adolescents plays a promising role in the field of pediatrics. Metabolomics has also been used to diagnose disease, discover novel biomarkers, and elucidate pathophysiological pathways. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. However, large-sample urinary metabolomic studies in children with ADHD are relatively rare. In this study, we aimed to identify specific biomarkers for ADHD diagnosis in children and adolescents by urinary metabolomic profiling. Methods We explored the urine metabolome in 363 healthy children aged 1-18 years and 76 patients with ADHD using high-resolution mass spectrometry. Results Metabolic pathways, such as arachidonic acid metabolism, steroid hormone biosynthesis, and catecholamine biosynthesis, were found to be related to sex and age in healthy children. The urinary metabolites displaying the largest differences between patients with ADHD and healthy controls belonged to the tyrosine, leucine, and fatty acid metabolic pathways. A metabolite panel consisting of FAPy-adenine, 3-methylazelaic acid, and phenylacetylglutamine was discovered to have good predictive ability for ADHD, with a receiver operating characteristic area under the curve (ROC-AUC) of 0.918. A panel of FAPy-adenine, N-acetylaspartylglutamic acid, dopamine 4-sulfate, aminocaproic acid, and asparaginyl-leucine was used to establish a robust model for ADHD comorbid tic disorders and controls with an AUC of 0.918.
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Affiliation(s)
- Xiaoyi Tian
- Department of Clinical Laboratory, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China
| | - Xiaoyan Liu
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Yan Wang
- Department of Clinical Laboratory, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Ying Liu
- Department of Clinical Laboratory, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Jie Ma
- Department of Clinical Laboratory, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Haidan Sun
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Jing Li
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Xiaoyue Tang
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Zhengguang Guo
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Wei Sun
- Proteomics Research Center, Institute of Basic Medical Sciences, School of Basic Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Jishui Zhang
- Department of Mental Health, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Wenqi Song
- Department of Clinical Laboratory, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China
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Marafi D, Fatih JM, Kaiyrzhanov R, Ferla MP, Gijavanekar C, Al-Maraghi A, Liu N, Sites E, Alsaif HS, Al-Owain M, Zakkariah M, El-Anany E, Guliyeva U, Guliyeva S, Gaba C, Haseeb A, Alhashem AM, Danish E, Karageorgou V, Beetz C, Subhi AA, Mullegama SV, Torti E, Sebastin M, Breilyn MS, Duberstein S, Abdel-Hamid MS, Mitani T, Du H, Rosenfeld JA, Jhangiani SN, Coban Akdemir Z, Gibbs RA, Taylor JC, Fakhro KA, Hunter JV, Pehlivan D, Zaki MS, Gleeson JG, Maroofian R, Houlden H, Posey JE, Sutton VR, Alkuraya FS, Elsea SH, Lupski JR. Biallelic variants in SLC38A3 encoding a glutamine transporter cause epileptic encephalopathy. Brain 2022; 145:909-924. [PMID: 34605855 PMCID: PMC9050560 DOI: 10.1093/brain/awab369] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/13/2021] [Accepted: 08/26/2021] [Indexed: 11/14/2022] Open
Abstract
The solute carrier (SLC) superfamily encompasses >400 transmembrane transporters involved in the exchange of amino acids, nutrients, ions, metals, neurotransmitters and metabolites across biological membranes. SLCs are highly expressed in the mammalian brain; defects in nearly 100 unique SLC-encoding genes (OMIM: https://www.omim.org) are associated with rare Mendelian disorders including developmental and epileptic encephalopathy and severe neurodevelopmental disorders. Exome sequencing and family-based rare variant analyses on a cohort with neurodevelopmental disorders identified two siblings with developmental and epileptic encephalopathy and a shared deleterious homozygous splicing variant in SLC38A3. The gene encodes SNAT3, a sodium-coupled neutral amino acid transporter and a principal transporter of the amino acids asparagine, histidine, and glutamine, the latter being the precursor for the neurotransmitters GABA and glutamate. Additional subjects with a similar developmental and epileptic encephalopathy phenotype and biallelic predicted-damaging SLC38A3 variants were ascertained through GeneMatcher and collaborations with research and clinical molecular diagnostic laboratories. Untargeted metabolomic analysis was performed to identify novel metabolic biomarkers. Ten individuals from seven unrelated families from six different countries with deleterious biallelic variants in SLC38A3 were identified. Global developmental delay, intellectual disability, hypotonia, and absent speech were common features while microcephaly, epilepsy, and visual impairment were present in the majority. Epilepsy was drug-resistant in half. Metabolomic analysis revealed perturbations of glutamate, histidine, and nitrogen metabolism in plasma, urine, and CSF of selected subjects, potentially representing biomarkers of disease. Our data support the contention that SLC38A3 is a novel disease gene for developmental and epileptic encephalopathy and illuminate the likely pathophysiology of the disease as perturbations in glutamine homeostasis.
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Affiliation(s)
- Dana Marafi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pediatrics, Faculty of Medicine, Kuwait University, P.O. Box 24923, 13110 Safat, Kuwait
- Correspondence to: Dana Marafi, MD, MSc Department of Pediatrics, Faculty of Medicine, Kuwait University P.O. Box 24923, 13110 Safat, Kuwait E-mail:
| | - Jawid M Fatih
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Rauan Kaiyrzhanov
- Department of Neuromuscular Disorders Institute of Neurology, University College London, Queen Square, London, UK
| | - Matteo P Ferla
- NIHR Oxford Biomedical Research Centre, Oxford OX4 2PG, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Charul Gijavanekar
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor Genetics Laboratory, Houston, TX 77030, USA
| | | | - Ning Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor Genetics Laboratory, Houston, TX 77030, USA
| | - Emily Sites
- Division of Molecular and Human Genetics, Nationwide Children's Hospital, Columbus, OH 43205, USA
| | - Hessa S Alsaif
- Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh 11211, Saudi Arabia
| | - Mohammad Al-Owain
- Department of Medical Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh 11211, Saudi Arabia
- Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University 11533, Riyadh, Saudi Arabia
| | - Mohamed Zakkariah
- Section of Child Neurology, Department of Pediatrics, Al-adan Hospital, Riqqa, Kuwait
| | - Ehab El-Anany
- Section of Child Neurology, Department of Pediatrics, Al-adan Hospital, Riqqa, Kuwait
| | | | | | - Colette Gaba
- Department of Pediatrics, Bon Secours Mercy Health, Toledo, OH 43608, USA
| | - Ateeq Haseeb
- Mercy Children’s Hospital, Toledo, OH 43608, USA
| | - Amal M Alhashem
- Division of Medical Genetic and Metabolic Medicine, Department of Pediatrics, Prince Sultan Medical Military City, Riyadh, Saudi Arabia
| | - Enam Danish
- Department of Ophthalmology, King Fahad Armed Forces Hospital, Jeddah, Saudi Arabia
| | | | | | - Alaa A Subhi
- Neurosciences Department, King Faisal Specialist Hospital and Research Center, Jeddah, Saudi Arabia
| | | | | | - Monisha Sebastin
- Albert Einstein College of Medicine and the Children's Hospital at Montefiore, Bronx, New York 10467, USA
- Division of Genetics, Department of Pediatrics, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, New York, 10467, USA
| | - Margo Sheck Breilyn
- Albert Einstein College of Medicine and the Children's Hospital at Montefiore, Bronx, New York 10467, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Susan Duberstein
- Isabelle Rapin Division of Child Neurology in the Saul R Korey Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Mohamed S Abdel-Hamid
- Department of Medical Molecular Genetics, Human Genetics and Genome Research Division, National Research Centre, Cairo, Egypt
| | - Tadahiro Mitani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Haowei Du
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor Genetics Laboratory, Houston, TX 77030, USA
| | - Shalini N Jhangiani
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Zeynep Coban Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jenny C Taylor
- NIHR Oxford Biomedical Research Centre, Oxford OX4 2PG, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Khalid A Fakhro
- Department of Human Genetics, Sidra Medicine, Doha 26999, Qatar
- Department of Genetic Medicine, Weill Cornell Medical College, Doha, Qatar
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha 34110, Qatar
| | - Jill V Hunter
- E.B. Singleton Department of Pediatric Radiology, Texas Children’s Hospital, Houston, TX 77030, USA
- Department of Radiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Davut Pehlivan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
- Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Maha S Zaki
- Department of Clinical Genetics, Human Genetics and Genome Research Division, National Research Centre, Cairo, Egypt
| | - Joseph G Gleeson
- Rady Children's Institute for Genomic Medicine, Howard Hughes Medical Institute, University of California, San Diego, CA 92123, USA
| | - Reza Maroofian
- Department of Neuromuscular Disorders Institute of Neurology, University College London, Queen Square, London, UK
| | - Henry Houlden
- Department of Neuromuscular Disorders Institute of Neurology, University College London, Queen Square, London, UK
| | - Jennifer E Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - V Reid Sutton
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor Genetics Laboratory, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
| | - Fowzan S Alkuraya
- Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh 11211, Saudi Arabia
| | - Sarah H Elsea
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor Genetics Laboratory, Houston, TX 77030, USA
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
- Correspondence may also be addressed to: James R. Lupski, MD, PhD, DSc (hon) Department of Molecular and Human Genetics, Baylor College of Medicine One Baylor Plaza, Room 604B, Houston, TX 77030, USA E-mail:
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21
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Marcotulli D, Davico C, Somà A, Teghille G, Ravaglia G, Amianto F, Ricci F, Puccinelli MP, Spada M, Vitiello B. Association between EEG Paroxysmal Abnormalities and Levels of Plasma Amino Acids and Urinary Organic Acids in Children with Autism Spectrum Disorder. CHILDREN (BASEL, SWITZERLAND) 2022; 9:540. [PMID: 35455584 PMCID: PMC9031943 DOI: 10.3390/children9040540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/30/2022] [Accepted: 04/05/2022] [Indexed: 11/21/2022]
Abstract
Abnormalities in the plasma amino acid and/or urinary organic acid profile have been reported in autism spectrum disorder (ASD). An imbalance between excitatory and inhibitory neuronal activity has been proposed as a mechanism to explain dysfunctional brain networks in ASD, as also suggested by the increased risk of epilepsy in this disorder. This study explored the possible association between presence of EEG paroxysmal abnormalities and the metabolic profile of plasma amino acids and urinary organic acids in children with ASD. In a sample of 55 children with ASD (81.8% male, mean age 53.67 months), EEGs were recorded, and 24 plasma amino acids and 56 urinary organic acids analyzed. EEG epileptiform discharges were found in 36 (65%) children. A LASSO regression, adjusted by age and sex, was applied to evaluate the association of plasma amino acids and urinary organic acids profiles with the presence of EEG epileptiform discharges. Plasma levels of threonine (THR) (coefficient = -0.02, p = 0.04) and urinary concentration of 3-Hydroxy-3-Methylglutaric acid (HMGA) (coefficient = 0.04, p = 0.02) were found to be associated with the presence of epileptiform discharges. These results suggest that altered redox mechanisms might be linked to epileptiform brain activity in ASD.
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Affiliation(s)
- Daniele Marcotulli
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Chiara Davico
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Alessandra Somà
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Guido Teghille
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Giorgio Ravaglia
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Federico Amianto
- Department of Neuroscience, University of Turin, 10126 Turin, Italy;
| | - Federica Ricci
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
| | - Maria Paola Puccinelli
- Department of Clinical Biochemistry, “Baldi e Riberi” Laboratory, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy;
| | - Marco Spada
- Section of Pediatrics, Department of Public Health and Pediatric Sciences, University of Torino, 10126 Turin, Italy;
| | - Benedetto Vitiello
- Section of Child and Adolescent Neuropsychiatry, Department of Public Health and Pediatric Sciences, University of Turin, 10126 Turin, Italy; (D.M.); (A.S.); (G.T.); (G.R.); (F.R.); (B.V.)
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22
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Ford L, Mitchell M, Wulff J, Evans A, Kennedy A, Elsea S, Wittmann B, Toal D. Clinical metabolomics for inborn errors of metabolism. Adv Clin Chem 2022; 107:79-138. [PMID: 35337606 DOI: 10.1016/bs.acc.2021.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Metabolism is a highly regulated process that provides nutrients to cells and essential building blocks for the synthesis of protein, DNA and other macromolecules. In healthy biological systems, metabolism maintains a steady state in which the concentrations of metabolites are relatively constant yet are subject to metabolic demands and environmental stimuli. Rare genetic disorders, such as inborn errors of metabolism (IEM), cause defects in regulatory enzymes or proteins leading to metabolic pathway disruption and metabolite accumulation or deficiency. Traditionally, the laboratory diagnosis of IEMs has been limited to analytical methods that target specific metabolites such as amino acids and acyl carnitines. This approach is effective as a screening method for the most common IEM disorders but lacks the comprehensive coverage of metabolites that is necessary to identify rare disorders that present with nonspecific clinical symptoms. Fortunately, advancements in technology and data analytics has introduced a new field of study called metabolomics which has allowed scientists to perform comprehensive metabolite profiling of biological systems to provide insight into mechanism of action and gene function. Since metabolomics seeks to measure all small molecule metabolites in a biological specimen, it provides an innovative approach to evaluating disease in patients with rare genetic disorders. In this review we provide insight into the appropriate application of metabolomics in clinical settings. We discuss the advantages and limitations of the method and provide details related to the technology, data analytics and statistical modeling required for metabolomic profiling of patients with IEMs.
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Affiliation(s)
- Lisa Ford
- Metabolon, Inc., Morrisville, NC, United States
| | | | - Jacob Wulff
- Metabolon, Inc., Morrisville, NC, United States
| | - Annie Evans
- Metabolon, Inc., Morrisville, NC, United States
| | | | - Sarah Elsea
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | | | - Douglas Toal
- Metabolon, Inc., Morrisville, NC, United States.
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23
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Bennett DH, Busgang SA, Kannan K, Parsons PJ, Takazawa M, Palmer CD, Schmidt RJ, Doucette JT, Schweitzer JB, Gennings C, Hertz-Picciotto I. Environmental exposures to pesticides, phthalates, phenols and trace elements are associated with neurodevelopment in the CHARGE study. ENVIRONMENT INTERNATIONAL 2022; 161:107075. [PMID: 35085933 PMCID: PMC9317896 DOI: 10.1016/j.envint.2021.107075] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 12/21/2021] [Accepted: 12/31/2021] [Indexed: 05/11/2023]
Abstract
OBJECTIVE To determine if higher exposures measured in early childhood to environmental phenols, phthalates, pesticides, and/or trace elements, are associated with increased odds of having a diagnosis of Autism Spectrum Disorder (ASD), Developmental Delay (DD), or Other Early Concerns (OEC) compared to typically developing children (TD). METHODS This study included 627 children between the ages of 2-5 who participated in the Childhood Autism Risks from Genetics and Environment (CHARGE) study. Urine samples were collected at the same study visit where diagnostic assessments to confirm diagnosis indicated during the recruitment process were performed. Adjusted multinomial regression models of each chemical with diagnosis as the outcome were conducted. Additionally, two methods were used to analyze mixtures: repeated holdout multinomial weighted quantile sum (WQS) regression for each chemical class; and a total urinary mixture effect was assessed with repeated holdout random subset WQS. RESULTS Many urinary chemicals were associated with increased odds of ASD, DD or OEC compared to TD; however, most did not remain significant after false discovery rate adjustment. Repeated holdout WQS indices provided evidence for associations of both a phenol/paraben mixture effect and a trace element mixture effect on DD independently. In analyses adjusted for confounders and other exposures, results suggested an association of a pesticide mixture effect with increased risk for ASD. Results also suggested associations of a total urinary mixture with greater odds of both ASD and DD separately. CONCLUSION Higher concentrations of urinary biomarkers were associated with ASD, DD, and OEC compared to TD, with consistency of the results comparing single chemical analyses and mixture analyses. Given that the biospecimens used for chemical analysis were generally collected many months after diagnoses were made, the direction of any causal association is unknown. Hence findings may reflect higher exposures among children with non-typical development than TD children due to differences in behaviors, metabolism, or toxicokinetics.
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Affiliation(s)
- Deborah H Bennett
- Department of Public Health Sciences, School of Medicine, University of California at Davis (UC Davis), Davis, CA, USA.
| | - Stefanie A Busgang
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kurunthachalam Kannan
- Division of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Albany, NY, USA; Department of Environmental Health Sciences, University at Albany, State University of New York, Albany, NY, USA; Department of Pediatrics and Department of Environmental Medicine, New York University School of Medicine, New York, NY, USA
| | - Patrick J Parsons
- Division of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Albany, NY, USA; Department of Environmental Health Sciences, University at Albany, State University of New York, Albany, NY, USA
| | - Mari Takazawa
- Division of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Christopher D Palmer
- Division of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Albany, NY, USA; Department of Environmental Health Sciences, University at Albany, State University of New York, Albany, NY, USA
| | - Rebecca J Schmidt
- Department of Public Health Sciences, School of Medicine, University of California at Davis (UC Davis), Davis, CA, USA; UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Sacramento, CA, USA
| | - John T Doucette
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julie B Schweitzer
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Sacramento, CA, USA; Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California at Davis (UC Davis), Sacramento, CA, USA
| | - Chris Gennings
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, School of Medicine, University of California at Davis (UC Davis), Davis, CA, USA; UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Sacramento, CA, USA
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24
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Mousa WK, Chehadeh F, Husband S. Recent Advances in Understanding the Structure and Function of the Human Microbiome. Front Microbiol 2022; 13:825338. [PMID: 35185849 PMCID: PMC8851206 DOI: 10.3389/fmicb.2022.825338] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/11/2022] [Indexed: 12/11/2022] Open
Abstract
Trillions of microbes live within our bodies in a deep symbiotic relationship. Microbial populations vary across body sites, driven by differences in the environment, immunological factors, and interactions between microbial species. Major advances in genome sequencing enable a better understanding of microbiome composition. However, most of the microbial taxa and species of the human microbiome are still unknown. Without revealing the identity of these microbes as a first step, we cannot appreciate their role in human health and diseases. A shift in the microbial balance, termed dysbiosis, is linked to a broad range of diseases from simple colitis and indigestion to cancer and dementia. The last decade has witnessed an explosion in microbiome research that led to a better understanding of the microbiome structure and function. This understanding leads to potential opportunities to develop next-generation microbiome-based drugs and diagnostic biomarkers. However, our understanding is limited given the highly personalized nature of the microbiome and its complex and multidirectional interactions with the host. In this review, we discuss: (1) our current knowledge of microbiome structure and factors that shape the microbial composition, (2) recent associations between microbiome dysbiosis and diseases, and (3) opportunities of new microbiome-based therapeutics. We analyze common themes, promises, gaps, and challenges of the microbiome research.
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Affiliation(s)
- Walaa K. Mousa
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain, United Arab Emirates
- Department of Biology, Whitman College, Walla Walla, WA, United States
- College of Pharmacy, Mansoura University, Mansoura, Egypt
| | - Fadia Chehadeh
- Department of Biology, Whitman College, Walla Walla, WA, United States
| | - Shannon Husband
- Department of Biology, Whitman College, Walla Walla, WA, United States
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25
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Marx W, Thomson S, O'Hely M, Symeonides C, Collier F, Tang MLK, Loughman A, Burgner D, Saffery R, Pham C, Mansell T, Sly PD, Vuillermin P, Ranganathan S, Ponsonby AL. Maternal inflammatory and omega-3 fatty acid pathways mediate the association between socioeconomic disadvantage and childhood cognition. Brain Behav Immun 2022; 100:211-218. [PMID: 34896180 DOI: 10.1016/j.bbi.2021.12.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/28/2021] [Accepted: 12/03/2021] [Indexed: 10/19/2022] Open
Abstract
Poor cognitive outcomes in early childhood predict poor educational outcomes and diminished health over the life course. We sought to investigate (i) whether maternal metabolites predict child cognition, and (ii) if maternal metabolomic profile mediates the relationship between environmental exposures and child cognition. Metabolites were measured using nuclear magnetic resonance-based metabolomics in pregnant women from a population-derived birth cohort. Child cognition was measured at age 2 years. In 662 mother-child pairs, elevated inflammatory markers (β = -2.62; 95% CI -4.10, -1.15; P = 0.0005) and lower omega-3 fatty acid-related metabolites (β = 0.49; 95% CI 0.09, 0.88; P = 0.02) in the mother were associated with lower child cognition and partially mediated the association between lower child cognition and multiple risk factors common to socioeconomic disadvantage. Modifying maternal prenatal metabolic pathways related to inflammation and omega-3 fatty acids may offset the adverse associations between prenatal risk factors related to socioeconomic disadvantage and low child cognition.
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Affiliation(s)
- Wolfgang Marx
- Florey Institute for Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia; Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, 299 Ryrie Street, Geelong, VIC 3220, Australia
| | - Sarah Thomson
- Florey Institute for Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia
| | - Martin O'Hely
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, 299 Ryrie Street, Geelong, VIC 3220, Australia; Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia
| | - Christos Symeonides
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; Minderoo Foundation, Perth, VIC 6000, Australia; Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia
| | - Fiona Collier
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, 299 Ryrie Street, Geelong, VIC 3220, Australia
| | - Mimi L K Tang
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
| | - Amy Loughman
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, 299 Ryrie Street, Geelong, VIC 3220, Australia
| | - David Burgner
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
| | - Cindy Pham
- Florey Institute for Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia; Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia
| | - Toby Mansell
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
| | - Peter D Sly
- Child Health Research Centre, The University of Queensland, 62 Graham St, South Brisbane, QLD 4101, Australia
| | - Peter Vuillermin
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, 299 Ryrie Street, Geelong, VIC 3220, Australia; Barwon Health, Bellerine St, Geelong, VIC 3220, Australia
| | - Sarath Ranganathan
- Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia
| | - Anne-Louise Ponsonby
- Florey Institute for Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia; Murdoch Children's Research Institute, Royal Children's Hospital, 50 Flemington Rd, Parkville, VIC 3052, Australia.
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26
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Alteration of the Intestinal Permeability Are Reflected by Changes in the Urine Metabolome of Young Autistic Children: Preliminary Results. Metabolites 2022; 12:metabo12020104. [PMID: 35208179 PMCID: PMC8875518 DOI: 10.3390/metabo12020104] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 12/11/2022] Open
Abstract
Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2–12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites—namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.
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Odom JD, Sutton VR. Metabolomics in Clinical Practice: Improving Diagnosis and Informing Management. Clin Chem 2021; 67:1606-1617. [PMID: 34633032 DOI: 10.1093/clinchem/hvab184] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 08/17/2021] [Indexed: 11/14/2022]
Abstract
BACKGROUND Metabolomics is the study of small molecules to simultaneously identify multiple low molecular weight molecules in a system. Broadly speaking, metabolomics can be subdivided into targeted and untargeted types of analysis, each type having advantages and drawbacks. Targeted metabolomics can quantify analytes but only looks for known or expected analytes related to particular disease(s), whereas untargeted metabolomics is typically nonquantitative but can detect thousands of analytes from an agnostic or nonhypothesis driven perspective, allowing for novel discoveries. CONTENT One application of metabolomics is the study of inborn errors of metabolism (IEM). The biochemical hallmark of IEMs is decreased concentrations of analytes distal to the enzymatic defect and buildup of analytes proximal to the defect. Metabolomics can detect these changes with one test and is effective in screening for and diagnosis of IEMs. Metabolomics has also been used to study many nonmetabolic diseases such as autism spectrum disorder, various cancers, and multiple congenital anomalies syndromes. Metabolomics has led to the discovery of many novel biomarkers of disease. Recent publications demonstrate how metabolomics can be useful clinically in the diagnosis and management of patients, as well as for research and clinical discovery. SUMMARY Metabolomics has proved to be a useful tool clinically for screening and diagnostic purposes and from a research perspective for the detection of novel biomarkers. In the future, metabolomics will likely become a routine part of the evaluation for many diseases as either a supplementary test or it may simply replace historical analyses that require several individual tests and sample types.
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Affiliation(s)
- John D Odom
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - V Reid Sutton
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX.,Baylor Genetics Laboratory, Houston, TX
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Likhitweerawong N, Thonusin C, Boonchooduang N, Louthrenoo O, Nookaew I, Chattipakorn N, Chattipakorn SC. Profiles of urine and blood metabolomics in autism spectrum disorders. Metab Brain Dis 2021; 36:1641-1671. [PMID: 34338974 PMCID: PMC8502415 DOI: 10.1007/s11011-021-00788-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 07/01/2021] [Indexed: 01/06/2023]
Abstract
Early diagnosis and treatment for autism spectrum disorder (ASD) pose challenges. The current diagnostic approach for ASD is mainly clinical assessment of patient behaviors. Biomarkers-based identification of ASD would be useful for pediatricians. Currently, there is no specific treatment for ASD, and evidence for the efficacy of alternative treatments remains inconclusive. The prevalence of ASD is increasing, and it is becoming more urgent to find the pathogenesis of such disorder. Metabolomic studies have been used to deeply investigate the alteration of metabolic pathways, including those associated with ASD. Metabolomics is a promising tool for identifying potential biomarkers and possible pathogenesis of ASD. This review comprehensively summarizes and discusses the abnormal metabolic pathways in ASD children, as indicated by evidence from metabolomic studies in urine and blood. In addition, the targeted interventions that could correct the metabolomic profiles relating to the improvement of autistic behaviors in affected animals and humans have been included. The results revealed that the possible underlying pathophysiology of ASD were alterations of amino acids, reactive oxidative stress, neurotransmitters, and microbiota-gut-brain axis. The potential common pathways shared by animal and human studies related to the improvement of ASD symptoms after pharmacological interventions were mammalian-microbial co-metabolite, purine metabolism, and fatty acid oxidation. The content of this review may contribute to novel biomarkers for the early diagnosis of ASD and possible therapeutic paradigms.
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Affiliation(s)
- Narueporn Likhitweerawong
- Division of Growth and Development, Department of Pediatrics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Chanisa Thonusin
- Neurophysiology Unit, Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, 110 Inthawarorot Road, Sriphum, Muang, Chiang Mai 50200, Thailand
- Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand
| | - Nonglak Boonchooduang
- Division of Growth and Development, Department of Pediatrics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Orawan Louthrenoo
- Division of Growth and Development, Department of Pediatrics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Intawat Nookaew
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Arkanasa, USA
| | - Nipon Chattipakorn
- Neurophysiology Unit, Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, 110 Inthawarorot Road, Sriphum, Muang, Chiang Mai 50200, Thailand
- Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand
| | - Siriporn C. Chattipakorn
- Neurophysiology Unit, Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, 110 Inthawarorot Road, Sriphum, Muang, Chiang Mai 50200, Thailand
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand
- Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai, Thailand
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Bam S, Buchanan E, Mahony C, O'Ryan C. DNA Methylation of PGC-1α Is Associated With Elevated mtDNA Copy Number and Altered Urinary Metabolites in Autism Spectrum Disorder. Front Cell Dev Biol 2021; 9:696428. [PMID: 34381777 PMCID: PMC8352569 DOI: 10.3389/fcell.2021.696428] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/05/2021] [Indexed: 12/12/2022] Open
Abstract
Autism spectrum disorder (ASD) is a complex disorder that is underpinned by numerous dysregulated biological pathways, including pathways that affect mitochondrial function. Epigenetic mechanisms contribute to this dysregulation and DNA methylation is an important factor in the etiology of ASD. We measured DNA methylation of peroxisome proliferator-activated receptor-gamma coactivator-1 alpha (PGC-1α), as well as five genes involved in regulating mitochondrial homeostasis to examine mitochondrial dysfunction in an ASD cohort of South African children. Using targeted Next Generation bisulfite sequencing, we found differential methylation (p < 0.05) at six key genes converging on mitochondrial biogenesis, fission and fusion in ASD, namely PGC-1α, STOML2, MFN2, FIS1, OPA1, and GABPA. PGC-1α, the transcriptional regulator of biogenesis, was significantly hypermethylated at eight CpG sites in the gene promoter, one of which contained a putative binding site for CAMP response binding element 1 (CREB1) (p = 1 × 10–6). Mitochondrial DNA (mtDNA) copy number, a marker of mitochondrial function, was elevated (p = 0.002) in ASD compared to controls and correlated significantly with DNA methylation at the PGC-1α promoter and there was a positive correlation between methylation at PGC-1α CpG#1 and mtDNA copy number (Spearman’s r = 0.2, n = 49, p = 0.04) in ASD. Furthermore, DNA methylation at PGC-1α CpG#1 and mtDNA copy number correlated significantly (p < 0.05) with levels of urinary organic acids associated with mitochondrial dysfunction, oxidative stress, and neuroendocrinology. Our data show differential methylation in ASD at six key genes converging on PGC-1α-dependent regulation of mitochondrial biogenesis and function. We demonstrate that methylation at the PGC-1α promoter is associated with elevated mtDNA copy number and metabolomic evidence of mitochondrial dysfunction in ASD. This highlights an unexplored role for DNA methylation in regulating specific pathways involved in mitochondrial biogenesis, fission and fusion contributing to mitochondrial dysfunction in ASD.
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Affiliation(s)
- Sophia Bam
- Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa
| | - Erin Buchanan
- Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa
| | - Caitlyn Mahony
- Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa
| | - Colleen O'Ryan
- Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa
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Alterations in Gut Vitamin and Amino Acid Metabolism are Associated with Symptoms and Neurodevelopment in Children with Autism Spectrum Disorder. J Autism Dev Disord 2021; 52:3116-3128. [PMID: 34263410 PMCID: PMC9213278 DOI: 10.1007/s10803-021-05066-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/02/2021] [Indexed: 01/01/2023]
Abstract
Metabolic disturbance may be implicated in the pathogenesis of autism. This study aimed to investigate the gut metabolomic profiles of autistic children and to analyze potential interaction between gut metabolites with autistic symptoms and neurodevelopment levels. We involved 120 autistic and 60 neurotypical children. Autistic symptoms and neurodevelopment levels were assessed. Fecal samples were analyzed using untargeted liquid chromatography-tandem mass spectrometry methods. Our results showed the metabolic disturbances of autistic children involved in multiple vitamin and amino acid metabolism pathways, with the strongest enrichment identified for tryptophan metabolism, retinol metabolism, cysteine-methionine metabolism, and vitamin digestion and absorption. Differential gut metabolites were correlated to autistic symptoms and neurodevelopment levels. Our findings improved the understanding of the perturbations of metabolome networks in autism.
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Courraud J, Ernst M, Svane Laursen S, Hougaard DM, Cohen AS. Studying Autism Using Untargeted Metabolomics in Newborn Screening Samples. J Mol Neurosci 2021; 71:1378-1393. [PMID: 33515432 PMCID: PMC8233278 DOI: 10.1007/s12031-020-01787-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 12/30/2020] [Indexed: 12/13/2022]
Abstract
Main risk factors of autism spectrum disorder (ASD) include both genetic and non-genetic factors, especially prenatal and perinatal events. Newborn screening dried blood spot (DBS) samples have great potential for the study of early biochemical markers of disease. To study DBS strengths and limitations in the context of ASD research, we analyzed the metabolomic profiles of newborns later diagnosed with ASD. We performed LC-MS/MS-based untargeted metabolomics on DBS from 37 case-control pairs randomly selected from the iPSYCH sample. After preprocessing using MZmine 2.41, metabolites were putatively annotated using mzCloud, GNPS feature-based molecular networking, and MolNetEnhancer. A total of 4360 mass spectral features were detected, of which 150 (113 unique) could be putatively annotated at a high confidence level. Chemical structure information at a broad level could be retrieved for 1009 metabolites, covering 31 chemical classes. Although no clear distinction between cases and controls was revealed, our method covered many metabolites previously associated with ASD, suggesting that biochemical markers of ASD are present at birth and may be monitored during newborn screening. Additionally, we observed that gestational age, age at sampling, and month of birth influence the metabolomic profiles of newborn DBS, which informs us on the important confounders to address in future studies.
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Affiliation(s)
- Julie Courraud
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen S, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Fuglesangs Allé 26, 8210, Aarhus, Denmark.
| | - Madeleine Ernst
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen S, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Fuglesangs Allé 26, 8210, Aarhus, Denmark
| | - Susan Svane Laursen
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen S, Denmark
| | - David M Hougaard
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen S, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Fuglesangs Allé 26, 8210, Aarhus, Denmark
| | - Arieh S Cohen
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Artillerivej 5, 2300, Copenhagen S, Denmark
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Campbell KA, Hickman R, Fallin MD, Bakulski KM. Prenatal exposure to metals and autism spectrum disorder: Current status and future directions. CURRENT OPINION IN TOXICOLOGY 2021; 26:39-48. [PMID: 39119269 PMCID: PMC11309009 DOI: 10.1016/j.cotox.2021.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with genetic and environmental contributors to etiology. Many metals have the potential to be neurotoxic and their exposures are widespread. The field of metals exposure and ASD research is emerging, and in this review article we assess the current state of the literature, with emphasis on the previous two years. Epidemiology studies are discussed with respect to exposure timing, exposure matrix, and outcome assessment. Toxicology studies are described for exposure dosing and timing, as well as behavioral and molecular outcomes. Further epidemiological and toxicological investigations can identify the timing and importance of metals as ASD risk factors and uncover biological mechanisms for risk mitigation and therapeutic strategies.
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Affiliation(s)
- Kyle A. Campbell
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Ruby Hickman
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - M. Daniele Fallin
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kelly M. Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
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Shackleton GL. Towards a biochemical approach to occupational stress management. Heliyon 2021; 7:e07175. [PMID: 34141933 PMCID: PMC8187824 DOI: 10.1016/j.heliyon.2021.e07175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 10/04/2020] [Accepted: 05/26/2021] [Indexed: 12/11/2022] Open
Abstract
Given the immense and growing cost of occupational stress to society through lost productivity and the burden to healthcare systems, current best practices for detecting, managing and reducing stress in the workplace are clearly sub-optimal and substantially better methods are required. Subjective, self-reported psychology and psychiatry-based instruments are prone to biases whereas current objective, biology-based measures produce conflicting results and are far from reliable. A multivariate approach to occupational stress research is required that reflects the broad, coordinated, physiological response to demands placed on the body by exposure to diverse occupational stressors. A literature review was conducted to determine the extent of application of the emerging multivariate technology of metabolomics to occupational stress research. Of 170 articles meeting the search criteria, three were identified that specifically studied occupational stressors using metabolomics. A further ten studies were not specifically occupational or were of indirect or peripheral relevance. The occupational studies, although limited in number highlight the technological challenges associated with the application of metabolomics to investigate occupational stress. They also demonstrate the utility to evaluate stress more comprehensively than univariate biomarker studies. The potential of this multivariate approach to enhance our understanding of occupational stress has yet to be established. This will require more studies with broader analytical coverage of the metabolome, longitudinal sampling, combination with experience sampling methods and comparison with psychometric models of occupational stress. Progress will likely involve combining multi-omic data into a holistic, systems biology approach to detecting, managing and reducing occupational stress and optimizing workplace performance.
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Žigman T, Petković Ramadža D, Šimić G, Barić I. Inborn Errors of Metabolism Associated With Autism Spectrum Disorders: Approaches to Intervention. Front Neurosci 2021; 15:673600. [PMID: 34121999 PMCID: PMC8193223 DOI: 10.3389/fnins.2021.673600] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/03/2021] [Indexed: 12/13/2022] Open
Abstract
Increasing evidence suggests that the autism spectrum disorder (ASD) may be associated with inborn errors of metabolism, such as disorders of amino acid metabolism and transport [phenylketonuria, homocystinuria, S-adenosylhomocysteine hydrolase deficiency, branched-chain α-keto acid dehydrogenase kinase deficiency, urea cycle disorders (UCD), Hartnup disease], organic acidurias (propionic aciduria, L-2 hydroxyglutaric aciduria), cholesterol biosynthesis defects (Smith-Lemli-Opitz syndrome), mitochondrial disorders (mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes-MELAS syndrome), neurotransmitter disorders (succinic semialdehyde dehydrogenase deficiency), disorders of purine metabolism [adenylosuccinate lyase (ADSL) deficiency, Lesch-Nyhan syndrome], cerebral creatine deficiency syndromes (CCDSs), disorders of folate transport and metabolism (cerebral folate deficiency, methylenetetrahydrofolate reductase deficiency), lysosomal storage disorders [Sanfilippo syndrome, neuronal ceroid lipofuscinoses (NCL), Niemann-Pick disease type C], cerebrotendinous xanthomatosis (CTX), disorders of copper metabolism (Wilson disease), disorders of haem biosynthesis [acute intermittent porphyria (AIP)] and brain iron accumulation diseases. In this review, we briefly describe etiology, clinical presentation, and therapeutic principles, if they exist, for these conditions. Additionally, we suggest the primary and elective laboratory work-up for their successful early diagnosis.
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Affiliation(s)
- Tamara Žigman
- Department of Paediatrics, University Hospital Center Zagreb and University of Zagreb School of Medicine, Zagreb, Croatia
| | - Danijela Petković Ramadža
- Department of Paediatrics, University Hospital Center Zagreb and University of Zagreb School of Medicine, Zagreb, Croatia
| | - Goran Šimić
- Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Ivo Barić
- Department of Paediatrics, University Hospital Center Zagreb and University of Zagreb School of Medicine, Zagreb, Croatia
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Murgia F, Gagliano A, Tanca MG, Or-Geva N, Hendren A, Carucci S, Pintor M, Cera F, Cossu F, Sotgiu S, Atzori L, Zuddas A. Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS). Front Neurosci 2021; 15:645267. [PMID: 34121984 PMCID: PMC8194687 DOI: 10.3389/fnins.2021.645267] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/27/2021] [Indexed: 01/21/2023] Open
Abstract
Introduction PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here, we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects. Design This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020. A PANS diagnosis was confirmed according to the PANS working criteria (National Institute of Mental Health [NIMH], 2010). Healthy age and sex-matched subjects were recruited as controls. Methods Thirty-four outpatients referred for PANS (mean age 9.5 years; SD 2.9, 71% male) and 25 neurotypical subjects matched for age and gender, were subjected to metabolite analysis. Serum samples were obtained from each participant and were analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiver Operator Curves (ROC) were performed. Results Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R2X = 0.44, R2Y = 0.54, Q2 = 0.44, p-value < 0.0001). The significantly altered variables were 2-Hydroxybutyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism, as well as glutamine and glutamate metabolism, exhibited the largest deviations from neurotypical controls. Conclusion We found a unique plasma metabolic profile in PANS patients, significantly differing from that of healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.
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Affiliation(s)
- Federica Murgia
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Antonella Gagliano
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Marcello G Tanca
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Noga Or-Geva
- Interdepartmental Program in Immunology, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Aran Hendren
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Sara Carucci
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Manuela Pintor
- Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Francesca Cera
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Fausto Cossu
- Paediatric Clinic, "A. Cao" Hospital, Cagliari, Italy
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Luigi Atzori
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessandro Zuddas
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
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Ustinova NV, Namazova-Baranova LS. Role of Pediatrician in Early Risk Evaluation, Diagnosis and Management of Children with Autism Spectrum Disorders. CURRENT PEDIATRICS 2021. [DOI: 10.15690/vsp.v20i2.2255] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The article discusses recent ideas about autism: classification approaches, incidence, etiology and pathogenesis, clinical manifestations and diagnosis, comorbid medical conditions, early detection approaches and medical care for children with autism spectrum disorders. The focus is on the information needed for pediatricians in their practice to provide effective medical care for children with neurodevelopmental disorders.
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Affiliation(s)
- Nataliya V. Ustinova
- Research Institute of Pediatrics and Children's Health in Central Clinical Hospital of the Russian Academy of Sciences; Scientific and Practical Center for Mental Health of Children and Adolescents n.a. G.E. Sukhareva
| | - Leyla S. Namazova-Baranova
- Research Institute of Pediatrics and Children's Health in Central Clinical Hospital of the Russian Academy of Sciences; Pirogov Russian National Research Medical University
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Kim JH, Yan Q, Uppal K, Cui X, Ling C, Walker DI, Heck JE, von Ehrenstein OS, Jones DP, Ritz B. Metabolomics analysis of maternal serum exposed to high air pollution during pregnancy and risk of autism spectrum disorder in offspring. ENVIRONMENTAL RESEARCH 2021; 196:110823. [PMID: 33548296 PMCID: PMC9059845 DOI: 10.1016/j.envres.2021.110823] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 01/27/2021] [Accepted: 01/27/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Previously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring. OBJECTIVES To identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD. METHODS We obtained stored mid-pregnancy serum from 214 mothers who lived in California's Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman's average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 μm) during the first trimester using the California Line Source Dispersion Model, version 4 (CALINE4). By utilizing liquid chromatography-high resolution mass spectrometry, we identified the metabolic profiles of maternal serum for 116 mothers with offspring who later developed ASD and 98 control mothers. Partial least squares discriminant analysis (PLS-DA) was employed to select metabolic features associated with air pollution exposure or autism risk in offspring. We also conducted extensive pathway enrichment analysis to elucidate potential ASD-related changes in the metabolome of pregnant women. RESULTS We extracted 4022 and 4945 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for potential confounders, we identified 167 and 222 discriminative features (HILIC and C18, respectively). Pathway enrichment analysis to discriminate metabolic features associated with ASD risk indicated various metabolic pathway perturbations linked to the tricarboxylic acid (TCA) cycle and mitochondrial function, including carnitine shuttle, amino acid metabolism, bile acid metabolism, and vitamin A metabolism. CONCLUSION Using high resolution metabolomics, we identified several metabolic pathways disturbed in mothers with ASD offspring among women experiencing high exposure to traffic-related air pollution during pregnancy that were associated with mitochondrial dysfunction. These findings provide us with a better understanding of metabolic disturbances involved in the development of ASD under adverse environmental conditions.
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Affiliation(s)
- Ja Hyeong Kim
- Department of Pediatrics, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, 44033, South Korea.
| | - Qi Yan
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
| | - Karan Uppal
- Computational Systems Medicine & Metabolomics Laboratory, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University, Atlanta, GA, 30322, USA.
| | - Xin Cui
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA; Perinatal Epidemiology and Health Outcomes Research Unit, Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children's Hospital, Palo Alto, CA, 94304, USA; California Perinatal Quality Care Collaborative, Palo Alto, CA, 94305, USA.
| | - Chenxiao Ling
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
| | - Douglas I Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Julia E Heck
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
| | - Ondine S von Ehrenstein
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA; Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
| | - Dean P Jones
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, School of Medicine, Emory University, Atlanta, GA, 30322, USA.
| | - Beate Ritz
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA; Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA; Department of Neurology, Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
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Yazd HS, Rubio VY, Chamberlain CA, Yost RA, Garrett TJ. Metabolomic and lipidomic characterization of an X-chromosome deletion disorder in neural progenitor cells by UHPLC-HRMS. J Mass Spectrom Adv Clin Lab 2021; 20:11-24. [PMID: 34820667 PMCID: PMC8601009 DOI: 10.1016/j.jmsacl.2021.05.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 05/05/2021] [Accepted: 05/24/2021] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION Intellectual disorders involving deletions of the X chromosome present a difficult task in the determination of a connection between symptoms and metabolites that could lead to treatment options. One specific disorder of X-chromosomal deletion, Fragile X syndrome, is the most frequently occurring of intellectual disabilities. Previous metabolomic studies have been limited to mouse models that may not have sufficiently revealed the full biochemical diversity of the disease in humans. OBJECTIVES The primary objective of this study was to elucidate the human biochemistry in X-chromosomal deletion disorders through metabolomic and lipidomic profiling, using cells from a X-deletion patient as a representative case. METHODS Metabolomic and lipidomic analysis was performed by UHPLC-HRMS on neural progenitor (NP) cells isolated from an afflicted female patient versus normal neural progenitor cells. RESULTS Results showed perturbations in several metabolic pathways, including those of arginine and proline, that significantly impact both neurotransmitter generation and overall brain function. Coincidently, dysregulation was observed for lipids involved in both cellular structure and membrane integrity. The trends of observed metabolomic changes, as well as lipidomic profiling from identified features, are discussed. CONCLUSION The lipidomic and metabolomic profiles of NP cell samples exhibited significant differentiation associated with partial deletion of the X chromosome. These findings suggest that rare X-chromosomal deletion disorders are not only a mental disorder limited to alterations in local neuronal functions, but are also metabolic diseases.
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Key Words
- BMP, Bis(monoacylglycero) phosphate
- Cer-NS, Ceramide nonhydroxyfatty acid-sphingosines
- Fragile X syndrome
- GL, Glycerolipid
- HexCer-NS, Hexosylceramide nonhydroxyfatty acid-sphingosines
- LPC, Lysophosphatidylcholines
- Lipidomics
- Metabolomics
- Microdeletion
- PC, Phosphatidylcholine
- PE, Phosphatidylethanolamine
- PG, Phosphatidylglycerol
- SM, Sphingomyelin
- SP, Sphingolipid
- ST, Sterol
- Xq27.3-Xq28
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Affiliation(s)
- Hoda Safari Yazd
- Department of Chemistry, University of Florida, Gainesville, FL 32610, USA
| | - Vanessa Y. Rubio
- Department of Chemistry, University of Florida, Gainesville, FL 32610, USA
- Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, NC 27412, USA
| | - Casey A. Chamberlain
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, USA
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Richard A. Yost
- Department of Chemistry, University of Florida, Gainesville, FL 32610, USA
| | - Timothy J. Garrett
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, USA
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Kato Y, Kuwabara H, Okada T, Munesue T, Benner S, Kuroda M, Kojima M, Yassin W, Eriguchi Y, Kameno Y, Murayama C, Nishimura T, Tsuchiya K, Kasai K, Ozaki N, Kosaka H, Yamasue H. Oxytocin-induced increase in N,N-dimethylglycine and time course of changes in oxytocin efficacy for autism social core symptoms. Mol Autism 2021; 12:15. [PMID: 33622389 PMCID: PMC7903697 DOI: 10.1186/s13229-021-00423-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 02/12/2021] [Indexed: 11/12/2022] Open
Abstract
Background Oxytocin is expected as a novel therapeutic agent for autism spectrum disorder (ASD) core symptoms. However, previous results on the efficacy of repeated administrations of oxytocin are controversial. Recently, we reported time-course changes in the efficacy of the neuropeptide underlying the controversial effects of repeated administration; however, the underlying mechanisms remained unknown. Methods The current study explored metabolites representing the molecular mechanisms of oxytocin’s efficacy using high-throughput metabolomics analysis on plasma collected before and after 6-week repeated intranasal administration of oxytocin (48 IU/day) or placebo in adult males with ASD (N = 106) who participated in a multi-center, parallel-group, double-blind, placebo-controlled, randomized controlled trial. Results Among the 35 metabolites measured, a significant increase in N,N-dimethylglycine was detected in the subjects administered oxytocin compared with those given placebo at a medium effect size (false discovery rate (FDR) corrected P = 0.043, d = 0.74, N = 83). Furthermore, subgroup analyses of the participants displaying a prominent time-course change in oxytocin efficacy revealed a significant effect of oxytocin on N,N-dimethylglycine levels with a large effect size (PFDR = 0.004, d = 1.13, N = 60). The increase in N,N-dimethylglycine was significantly correlated with oxytocin-induced clinical changes, assessed as changes in quantifiable characteristics of autistic facial expression, including both of improvements between baseline and 2 weeks (PFDR = 0.006, r = − 0.485, N = 43) and deteriorations between 2 and 4 weeks (PFDR = 0.032, r = 0.415, N = 37). Limitations The metabolites changes caused by oxytocin administration were quantified using peripheral blood and therefore may not directly reflect central nervous system changes. Conclusion Our findings demonstrate an association of N,N-dimethylglycine upregulation with the time-course change in the efficacy of oxytocin on autistic social deficits. Furthermore, the current findings support the involvement of the N-methyl-D-aspartate receptor and neural plasticity to the time-course change in oxytocin’s efficacy. Trial registration: A multi-center, parallel-group, placebo-controlled, double-blind, confirmatory trial of intranasal oxytocin in participants with autism spectrum disorders (the date registered: 30 October 2014; UMIN Clinical Trials Registry: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000017703) (UMIN000015264).
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Affiliation(s)
- Yasuhiko Kato
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan
| | - Hitoshi Kuwabara
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan
| | - Takashi Okada
- Department of Psychiatry, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
| | - Toshio Munesue
- Research Center for Child Mental Development, Kanazawa University, 13-1 Takara-machi, Kanazawa, 920-8640, Japan
| | - Seico Benner
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan
| | - Miho Kuroda
- Department of Child Neuropsychiatry, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Masaki Kojima
- Department of Child Neuropsychiatry, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Walid Yassin
- Department of Child Neuropsychiatry, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yosuke Eriguchi
- Department of Child Neuropsychiatry, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yosuke Kameno
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan
| | - Chihiro Murayama
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan
| | - Tomoko Nishimura
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka/Kanazawa/Hamamatsu/Chiba/Fukui, Japan
| | - Kenji Tsuchiya
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka/Kanazawa/Hamamatsu/Chiba/Fukui, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
| | - Hirotaka Kosaka
- Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Eiheiji, Fukui, 910-1193, Japan
| | - Hidenori Yamasue
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City, 431-3192, Japan. .,United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka/Kanazawa/Hamamatsu/Chiba/Fukui, Japan.
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Yin X, Altman T, Rutherford E, West KA, Wu Y, Choi J, Beck PL, Kaplan GG, Dabbagh K, DeSantis TZ, Iwai S. A Comparative Evaluation of Tools to Predict Metabolite Profiles From Microbiome Sequencing Data. Front Microbiol 2020; 11:595910. [PMID: 33343536 PMCID: PMC7746778 DOI: 10.3389/fmicb.2020.595910] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 11/16/2020] [Indexed: 12/26/2022] Open
Abstract
Metabolomic analyses of human gut microbiome samples can unveil the metabolic potential of host tissues and the numerous microorganisms they support, concurrently. As such, metabolomic information bears immense potential to improve disease diagnosis and therapeutic drug discovery. Unfortunately, as cohort sizes increase, comprehensive metabolomic profiling becomes costly and logistically difficult to perform at a large scale. To address these difficulties, we tested the feasibility of predicting the metabolites of a microbial community based solely on microbiome sequencing data. Paired microbiome sequencing (16S rRNA gene amplicons, shotgun metagenomics, and metatranscriptomics) and metabolome (mass spectrometry and nuclear magnetic resonance spectroscopy) datasets were collected from six independent studies spanning multiple diseases. We used these datasets to evaluate two reference-based gene-to-metabolite prediction pipelines and a machine-learning (ML) based metabolic profile prediction approach. With the pre-trained model on over 900 microbiome-metabolome paired samples, the ML approach yielded the most accurate predictions (i.e., highest F1 scores) of metabolite occurrences in the human gut and outperformed reference-based pipelines in predicting differential metabolites between case and control subjects. Our findings demonstrate the possibility of predicting metabolites from microbiome sequencing data, while highlighting certain limitations in detecting differential metabolites, and provide a framework to evaluate metabolite prediction pipelines, which will ultimately facilitate future investigations on microbial metabolites and human health.
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Affiliation(s)
| | - Tomer Altman
- Altman Analytics LLC, San Francisco, CA, United States
| | | | | | - Yonggan Wu
- Second Genome Inc., Brisbane, CA, United States
| | | | - Paul L. Beck
- Department of Medicine, University of Calgary, Calgary, AB, Canada
| | - Gilaad G. Kaplan
- Department of Medicine, University of Calgary, Calgary, AB, Canada
| | | | | | - Shoko Iwai
- Second Genome Inc., Brisbane, CA, United States
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Mussap M, Siracusano M, Noto A, Fattuoni C, Riccioni A, Rajula HSR, Fanos V, Curatolo P, Barberini L, Mazzone L. The Urine Metabolome of Young Autistic Children Correlates with Their Clinical Profile Severity. Metabolites 2020; 10:metabo10110476. [PMID: 33238400 PMCID: PMC7700197 DOI: 10.3390/metabo10110476] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 11/10/2020] [Accepted: 11/19/2020] [Indexed: 12/12/2022] Open
Abstract
Autism diagnosis is moving from the identification of common inherited genetic variants to a systems biology approach. The aims of the study were to explore metabolic perturbations in autism, to investigate whether the severity of autism core symptoms may be associated with specific metabolic signatures; and to examine whether the urine metabolome discriminates severe from mild-to-moderate restricted, repetitive, and stereotyped behaviors. We enrolled 57 children aged 2–11 years; thirty-one with idiopathic autism and twenty-six neurotypical (NT), matched for age and ethnicity. The urine metabolome was investigated by gas chromatography-mass spectrometry (GC-MS). The urinary metabolome of autistic children was largely distinguishable from that of NT children; food selectivity induced further significant metabolic differences. Severe autism spectrum disorder core deficits were marked by high levels of metabolites resulting from diet, gut dysbiosis, oxidative stress, tryptophan metabolism, mitochondrial dysfunction. The hierarchical clustering algorithm generated two metabolic clusters in autistic children: 85–90% of children with mild-to-moderate abnormal behaviors fell in cluster II. Our results open up new perspectives for the more general understanding of the correlation between the clinical phenotype of autistic children and their urine metabolome. Adipic acid, palmitic acid, and 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid can be proposed as candidate biomarkers of autism severity.
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Affiliation(s)
- Michele Mussap
- Department of Surgical Sciences, School of Medicine, University of Cagliari, 09042 Monserrato, Italy; (H.S.R.R.); (V.F.)
- Correspondence: ; Tel.: +39-070-51093403
| | - Martina Siracusano
- Department of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy;
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy
| | - Antonio Noto
- Department of Medical Sciences and Public Health, University of Cagliari, 09042 Monserrato, Italy; (A.N.); (L.B.)
| | - Claudia Fattuoni
- Department of Chemical and Geological Sciences, University of Cagliari, 09042 Monserrato, Italy;
| | - Assia Riccioni
- Child Neurology and Psychiatry Unit, System Medicine Department, Tor Vergata University Hospital of Rome, 00133 Rome, Italy; (A.R.); (P.C.); (L.M.)
| | - Hema Sekhar Reddy Rajula
- Department of Surgical Sciences, School of Medicine, University of Cagliari, 09042 Monserrato, Italy; (H.S.R.R.); (V.F.)
| | - Vassilios Fanos
- Department of Surgical Sciences, School of Medicine, University of Cagliari, 09042 Monserrato, Italy; (H.S.R.R.); (V.F.)
| | - Paolo Curatolo
- Child Neurology and Psychiatry Unit, System Medicine Department, Tor Vergata University Hospital of Rome, 00133 Rome, Italy; (A.R.); (P.C.); (L.M.)
| | - Luigi Barberini
- Department of Medical Sciences and Public Health, University of Cagliari, 09042 Monserrato, Italy; (A.N.); (L.B.)
| | - Luigi Mazzone
- Child Neurology and Psychiatry Unit, System Medicine Department, Tor Vergata University Hospital of Rome, 00133 Rome, Italy; (A.R.); (P.C.); (L.M.)
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Bjørklund G, Tinkov AA, Hosnedlová B, Kizek R, Ajsuvakova OP, Chirumbolo S, Skalnaya MG, Peana M, Dadar M, El-Ansary A, Qasem H, Adams JB, Aaseth J, Skalny AV. The role of glutathione redox imbalance in autism spectrum disorder: A review. Free Radic Biol Med 2020; 160:149-162. [PMID: 32745763 DOI: 10.1016/j.freeradbiomed.2020.07.017] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 07/02/2020] [Accepted: 07/13/2020] [Indexed: 12/22/2022]
Abstract
The role of glutathione in autism spectrum disorder (ASD) is emerging as a major topic, due to its role in the maintenance of the intracellular redox balance. Several studies have implicated glutathione redox imbalance as a leading factor in ASD, and both ASD and many other neurodevelopmental disorders involve low levels of reduced glutathione (GSH), high levels of oxidized glutathione (GSSG), and abnormalities in the expressions of glutathione-related enzymes in the blood or brain. Glutathione metabolism, through its impact on redox environment or redox-independent mechanisms, interferes with multiple mechanisms involved in ASD pathogenesis. Glutathione-mediated regulation of glutamate receptors [e.g., N-methyl-d-aspartate (NMDA) receptor], as well as the role of glutamate as a substrate for glutathione synthesis, may be involved in the regulation of glutamate excitotoxicity. However, the interaction between glutathione and glutamate in the pathogenesis of brain diseases may vary from synergism to antagonism. Modulation of glutathione is also associated with regulation of redox-sensitive transcription factors nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) and downstream signaling (proinflammatory cytokines and inducible enzymes), thus providing a significant impact on neuroinflammation. Mitochondrial dysfunction, as well as neuronal apoptosis, may also provide a significant link between glutathione metabolism and ASD. Furthermore, it has been recently highlighted that glutathione can affect and modulate DNA methylation and epigenetics. Review analysis including research studies meeting the required criteria for analysis showed statistically significant differences between the plasma GSH and GSSG levels as well as GSH:GSSG ratio in autistic patients compared with healthy individuals (P = 0.0145, P = 0.0150 and P = 0.0202, respectively). Therefore, the existing data provide a strong background on the role of the glutathione system in ASD pathogenesis. Future research is necessary to investigate the role of glutathione redox signaling in ASD, which could potentially also lead to promising therapeutics.
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Affiliation(s)
- Geir Bjørklund
- Council for Nutritional and Environmental Medicine (CONEM), Mo I Rana, Norway.
| | - Alexey A Tinkov
- IM Sechenov First Moscow State Medical University, Moscow, Russia; Yaroslavl State University, Yaroslavl, Russia; Federal Research Centre of Biological Systems, Agro-technologies of the Russian Academy of Sciences, Orenburg, Russia
| | - Božena Hosnedlová
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic; CONEM Metallomics Nanomedicine Research Group (CMNRG), Brno, Czech Republic
| | - Rene Kizek
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic; CONEM Metallomics Nanomedicine Research Group (CMNRG), Brno, Czech Republic; Faculty of Pharmacy with Division of Laboratory Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Olga P Ajsuvakova
- IM Sechenov First Moscow State Medical University, Moscow, Russia; Yaroslavl State University, Yaroslavl, Russia; Federal Research Centre of Biological Systems, Agro-technologies of the Russian Academy of Sciences, Orenburg, Russia
| | - Salvatore Chirumbolo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy; CONEM Scientific Secretary, Verona, Italy
| | - Margarita G Skalnaya
- IM Sechenov First Moscow State Medical University, Moscow, Russia; Federal Research Centre of Biological Systems, Agro-technologies of the Russian Academy of Sciences, Orenburg, Russia
| | | | - Maryam Dadar
- Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Afaf El-Ansary
- Medicinal Chemistry Department, King Saud University, Riyadh, Saudi Arabia; Autism Research and Treatment Center, Riyadh, Saudi Arabia; CONEM Saudi Autism Research Group, King Saud University, Riyadh, Saudi Arabia
| | - Hanan Qasem
- Autism Research and Treatment Center, Riyadh, Saudi Arabia; CONEM Saudi Autism Research Group, King Saud University, Riyadh, Saudi Arabia
| | - James B Adams
- School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA
| | - Jan Aaseth
- Research Department, Innlandet Hospital Trust, Brumunddal, Norway
| | - Anatoly V Skalny
- IM Sechenov First Moscow State Medical University, Moscow, Russia; Federal Research Centre of Biological Systems, Agro-technologies of the Russian Academy of Sciences, Orenburg, Russia
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Plasma metabolites in treatment-requiring retinopathy of prematurity: Potential biomarkers identified by metabolomics. Exp Eye Res 2020; 199:108198. [PMID: 32828955 DOI: 10.1016/j.exer.2020.108198] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 08/02/2020] [Accepted: 08/13/2020] [Indexed: 02/08/2023]
Abstract
Retinopathy of prematurity (ROP) is a potentially blinding condition caused by disruption of retinal vascularization and metabolism. This study aims to identify altered metabolites from plasma in patients with treatment-requiring ROP (TR-ROP) compared with controls. An untargeted metabolomics analysis was performed to reveal the metabolomic profiles of the plasma between TR-ROP patients (n = 38) and age-matched infants (n = 23). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the potential signaling pathways of the changed metabolites. Under positive ion mode, a total of 29 metabolites were significantly altered in plasma between TR-ROP patients and controls, and 23 altered metabolites were identified under negative ion mode. KEGG analyses indicated that "protein digestion and absorption" and "aminoacyl-tRNA biosynthesis" were the most enriched pathways of the altered metabolites. These results demonstrated that metabolomic profiles changed in plasma of TR-ROP, and the altered metabolites could be served as potential biomarkers for the diagnosis and prognosis of TR-ROP patients. Besides, the metabolomic profiles might provide clues to discover novel therapeutic strategies in ROP treatment.
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Smith AM, Natowicz MR, Braas D, Ludwig MA, Ney DM, Donley ELR, Burrier RE, Amaral DG. A Metabolomics Approach to Screening for Autism Risk in the Children's Autism Metabolome Project. Autism Res 2020; 13:1270-1285. [PMID: 32558271 PMCID: PMC7496373 DOI: 10.1002/aur.2330] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/28/2020] [Accepted: 06/03/2020] [Indexed: 12/18/2022]
Abstract
Autism spectrum disorder (ASD) is biologically and behaviorally heterogeneous. Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48 months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty-four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4-hydroxyproline, or α-ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%-57%) and 91% specificity (95% CI, 86%-94%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments. LAY SUMMARY: Analysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18 months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood-based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. Autism Res 2020, 13: 1270-1285. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.
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Affiliation(s)
- Alan M Smith
- Stemina Biomarker Discovery, Inc, Madison, Wisconsin, USA
| | - Marvin R Natowicz
- Pathology and Laboratory Medicine, Genomics, Neurology, and Pediatrics Institutes, Cleveland Clinic, Cleveland, Ohio, USA
| | - Daniel Braas
- Stemina Biomarker Discovery, Inc, Madison, Wisconsin, USA
| | | | - Denise M Ney
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | | | - David G Amaral
- The MIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, California, USA
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Abstract
In the last years, 'omics' technologies, and especially metabolomics, emerged as expanding scientific disciplines and promising technologies in the characterization of several pathophysiological processes.In detail, metabolomics, able to detect in a dynamic way the whole set of molecules of low molecular weight in cells, tissues, organs, and biological fluids, can provide a detailed phenotypic portray, representing a metabolic "snapshot."Thanks to its numerous strength points, metabolomics could become a fundamental tool in human health, allowing the exact evaluation of individual metabolic responses to pathophysiological stimuli including drugs, environmental changes, lifestyle, a great number of diseases and other epigenetics factors.Moreover, if current metabolomics data will be confirmed on larger samples, such technology could become useful in the early diagnosis of diseases, maybe even before the clinical onset, allowing a clinical monitoring of disease progression and helping in performing the best therapeutic approach, potentially predicting the therapy response and avoiding overtreatments. Moreover, the application of metabolomics in nutrition could provide significant information on the best nutrition regimen, optimal infantile growth and even in the characterization and improvement of commercial products' composition.These are only some of the fields in which metabolomics was applied, in the perspective of a precision-based, personalized care of human health.In this review, we discuss the available literature on such topic and provide some evidence regarding clinical application of metabolomics in heart diseases, auditory disturbance, nephrouropathies, adult and pediatric cancer, obstetrics, perinatal conditions like asphyxia, neonatal nutrition, neonatal sepsis and even some neuropsychiatric disorders, including autism.Our research group has been interested in metabolomics since several years, performing a wide spectrum of experimental and clinical studies, including the first metabolomics analysis of human breast milk. In the future, it is reasonable to predict that the current knowledge could be applied in daily clinical practice, and that sensible metabolomics biomarkers could be easily detected through cheap and accurate sticks, evaluating biofluids at the patient's bed, improving diagnosis, management and prognosis of sick patients and allowing a personalized medicine. A dream? May be I am a dreamer, but I am not the only one.
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Affiliation(s)
- Flaminia Bardanzellu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, SS 554 km 4,500, 09042, Monserrato, CA, Italy.
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, SS 554 km 4,500, 09042, Monserrato, CA, Italy
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García-Gutiérrez MS, Navarrete F, Sala F, Gasparyan A, Austrich-Olivares A, Manzanares J. Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality. Front Psychiatry 2020; 11:432. [PMID: 32499729 PMCID: PMC7243207 DOI: 10.3389/fpsyt.2020.00432] [Citation(s) in RCA: 121] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 04/28/2020] [Indexed: 12/12/2022] Open
Abstract
During the last years, an extraordinary effort has been made to identify biomarkers as potential tools for improving prevention, diagnosis, drug response and drug development in psychiatric disorders. Contrary to other diseases, mental illnesses are classified by diagnostic categories with a broad variety list of symptoms. Consequently, patients diagnosed from the same psychiatric illness present a great heterogeneity in their clinical presentation. This fact together with the incomplete knowledge of the neurochemical alterations underlying mental disorders, contribute to the limited efficacy of current pharmacological options. In this respect, the identification of biomarkers in psychiatry is becoming essential to facilitate diagnosis through the developing of markers that allow to stratify groups within the syndrome, which in turn may lead to more focused treatment options. In order to shed light on this issue, this review summarizes the concept and types of biomarkers including an operational definition for therapeutic development. Besides, the advances in this field were summarized and sorted into five categories, which include genetics, transcriptomics, proteomics, metabolomics, and epigenetics. While promising results were achieved, there is a lack of biomarker investigations especially related to treatment response to psychiatric conditions. This review includes a final conclusion remarking the future challenges required to reach the goal of developing valid, reliable and broadly-usable biomarkers for psychiatric disorders and their treatment. The identification of factors predicting treatment response will reduce trial-and-error switches of medications facilitating the discovery of new effective treatments, being a crucial step towards the establishment of greater personalized medicine.
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Affiliation(s)
- Maria Salud García-Gutiérrez
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Alicante, Spain.,Red Temática de Investigación Cooperativa en Salud (RETICS), Red de Trastornos Adictivos, Instituto de Salud Carlos III, MICINN and FEDER, Madrid, Spain
| | - Francisco Navarrete
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Alicante, Spain.,Red Temática de Investigación Cooperativa en Salud (RETICS), Red de Trastornos Adictivos, Instituto de Salud Carlos III, MICINN and FEDER, Madrid, Spain
| | - Francisco Sala
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Alicante, Spain
| | - Ani Gasparyan
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Alicante, Spain.,Red Temática de Investigación Cooperativa en Salud (RETICS), Red de Trastornos Adictivos, Instituto de Salud Carlos III, MICINN and FEDER, Madrid, Spain
| | | | - Jorge Manzanares
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Alicante, Spain.,Red Temática de Investigación Cooperativa en Salud (RETICS), Red de Trastornos Adictivos, Instituto de Salud Carlos III, MICINN and FEDER, Madrid, Spain
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