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      Inborn Errors of Metabolism Associated With Autism Spectrum Disorders: Approaches to Intervention

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          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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          Most cited references88

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          Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016

          Problem/Condition Autism spectrum disorder (ASD). Period Covered 2016. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public Health Action These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
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            Elevated immune response in the brain of autistic patients.

            This study determined immune activities in the brain of ASD patients and matched normal subjects by examining cytokines in the brain tissue. Our results showed that proinflammatory cytokines (TNF-alpha, IL-6 and GM-CSF), Th1 cytokine (IFN-gamma) and chemokine (IL-8) were significantly increased in the brains of ASD patients compared with the controls. However the Th2 cytokines (IL-4, IL-5 and IL-10) showed no significant difference. The Th1/Th2 ratio was also significantly increased in ASD patients. ASD patients displayed an increased innate and adaptive immune response through the Th1 pathway, suggesting that localized brain inflammation and autoimmune disorder may be involved in the pathogenesis of ASD.
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              Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions.

              The autism spectrum disorders are a collective of conditions that have in common impaired socialization and communication in association with stereotypic behaviors. The reported incidence of autism spectrum disorders has increased dramatically over the past two decades. In addition, increased attention has been paid to these conditions by both lay and professional groups. These trends have resulted in an increase in the number of referrals to clinical geneticist for the evaluation of persons with autism spectrum disorders. The primary roles of the geneticist in this process are to define etiology when possible, to provide genetic counseling, and to contribute to case management. In deciding on the appropriate evaluation for a particular patient, the geneticist will consider a host of factors: (i) ensuring an accurate diagnosis of autism before proceeding with any investigation; (ii) discussing testing options, diagnostic yields, and family investment before proceeding with an evaluation; (iii) communicating and coordinating with the patient-centered medical home (PCMH); (iv) assessing the continuously expanding and evolving list of available laboratory-testing modalities in light of the published literature; (v) recognizing the expanded phenotypes of well-described syndromic and metabolic conditions that overlap with autism spectrum disorders; and (vi) defining an individualized evaluation plan based on the unique history and clinical features of a given patient. The guidelines in this paper have been developed to assist the clinician in the consideration of these factors. It updates the original publication from 2008.Genet Med 2013:15(5):399-407.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                28 May 2021
                2021
                : 15
                : 673600
                Affiliations
                [1] 1Department of Paediatrics, University Hospital Center Zagreb and University of Zagreb School of Medicine , Zagreb, Croatia
                [2] 2Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine , Zagreb, Croatia
                Author notes

                Edited by: Joana M. Gaspar, Federal University of Santa Catarina, Brazil

                Reviewed by: William Griffiths, Swansea University, United Kingdom; Khue Vu Nguyen, University of California, San Diego, United States

                *Correspondence: Goran Šimić, gsimic@ 123456hiim.hr

                This article was submitted to Neuropharmacology, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2021.673600
                8193223
                34121999
                0325031a-d46f-4491-a6b2-f216661657ab
                Copyright © 2021 Žigman, Petković Ramadža, Šimić and Barić.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 27 February 2021
                : 03 May 2021
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 88, Pages: 11, Words: 0
                Funding
                Funded by: Hrvatska Zaklada za Znanost 10.13039/501100004488
                Funded by: European Regional Development Fund 10.13039/501100008530
                Categories
                Neuroscience
                Review

                Neurosciences
                autism spectrum disorder,early diagnosis,genetic testing,inborn errors of metabolism,therapeutic principles

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