scholarly journals Lactonase Activity and Lipoprotein-Phospholipase A2as Possible Novel Serum Biomarkers for the Differential Diagnosis of Autism Spectrum Disorders and Rett Syndrome: Results from a Pilot Study

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Joussef Hayek ◽  
Carlo Cervellati ◽  
Ilaria Crivellari ◽  
Alessandra Pecorelli ◽  
Giuseppe Valacchi
Keyword(s):  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Roc Analysis ◽  
Brain Dysfunction ◽  
Autism Spectrum ◽  
Serum Biomarkers ◽  
Paraoxonase 1 ◽  
Pairwise Comparisons ◽  
Spectrum Disorders ◽  
Operator Curve

Rett syndrome (RTT) and autism spectrum disorders (ASDs) are not merely expression of brain dysfunction but also reflect the perturbation of physiological/metabolic homeostasis. Accordingly, both disorders appear to be associated with increased vulnerability to toxicants produced by redox imbalance, inflammation, and pollution, and impairment of systemic-detoxifying agents could play a role in the exacerbation of these detrimental processes. To check this hypothesis, the activities of two mechanistically related blood-based enzymes, paraoxonase-1 (arylesterase, paraoxonase, and lactonase), and lipoprotein-associated phospholipase A2(Lp-PLA2) were measured in the serum of 79 ASD and 95 RTT patients, and 77 controls. Lactonase and Lp-PLA2showed a similar trend characterized by significantly lower levels of both activities in ASD compared to controls and RTT (p<0.001for all pairwise comparisons). Noteworthy, receiving operator curve (ROC) analysis revealed that lactonase and, mostly, Lp-PLA2were able to discriminate between ASD and controls (lactonase: area under curve, AUC = 0.660; Lp-PLA2, AUC = 0.780), and, considering only females, between ASD and RTT (lactonase, AUC = 0.714; Lp-PLA2, AUC = 0.881). These results suggest that lactonase and, especially, Lp-PLA2activities might represent novel candidate biomarkers for ASD.

scholarly journals Fatty Acids and Autism Spectrum Disorders: The Rett Syndrome Conundrum

2013 ◽  
Vol 04 (09) ◽  
pp. 71-75 ◽  
Author(s):  
Claudio De Felice ◽  
Cinzia Signorini ◽  
Silvia Leoncini ◽  
Alessandra Pecorelli ◽  
Thierry Durand ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Autism Spectrum ◽  
Spectrum Disorders

Dysregulated brain immunity and neurotrophin signaling in Rett syndrome and autism spectrum disorders

2015 ◽  
Vol 279 ◽  
pp. 33-38 ◽  
Author(s):  
Theoharis C. Theoharides ◽  
Marianna Athanassiou ◽  
Smaro Panagiotidou ◽  
Robert Doyle
Keyword(s):  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Autism Spectrum ◽  
Spectrum Disorders ◽  
Neurotrophin Signaling

Rett Syndrome: On Clinical and Genetic Features, and Experimental Models Based on MeCP2 Dysfunction

2013 ◽  
Author(s):  
Gaston Calfa ◽  
Alan K. Percy ◽  
Lucas Pozzo-Miller
Keyword(s):  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Autism Spectrum ◽  
Experimental Models ◽  
Genetic Features ◽  
Spectrum Disorders ◽  
Genetic Bases

Chapter 5 reviews the features of Rett syndrome (RTT) and its genetic bases, as well as the role of MECP2 in neurodevelopment at the clinical as well as molecular and cellular levels, exploring potential neurobiological mechanisms shared with other autism spectrum disorders.

scholarly journals Paraoxonase 1 activities and polymorphisms in autism spectrum disorders

2008 ◽  
Author(s):  
Sergiu P. Paşca ◽  
Eleonora Dronca ◽  
Bogdan Nemeş ◽  
Tamás Kaucsár ◽  
Emõke Endreffy ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Autism Spectrum ◽  
Paraoxonase 1 ◽  
Spectrum Disorders

PECULIARITIES OF EEG DIAGNOSTICS IN CHILDREN WITH AUTISM SPECTRUM DISORDERS

2021 ◽  
pp. 69-82
Author(s):  
D.I. Chizh ◽  
E.V. Petrova ◽  
V.S. Muzhikov ◽  
E.N. Obedkina
Keyword(s):  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Mirror Neurons ◽  
Alpha Rhythm ◽  
Autism Spectrum ◽  
Mu Rhythm ◽  
Brain Functioning ◽  
Spectrum Disorders ◽  
Autistic Disorders ◽  
The Brain

Autism spectrum disorders are now occupying an increasingly large niche among childhood diseases and, according to some experts, have the potential to become a pandemic. Unlike many other disorders, autism spectrum disorders do not have a clear, unified mechanism, either at the cellular, molecular or structural levels. Currently, much literature is devoted to this topic, but there is no scientific consensus about the true reason. Despite a similar clinical picture, the etiopathogenetic mechanisms of these disorders can be different: from dysontogenesis and genetic mutations to exogenous factors. This article presents EEG patterns for various phenotypes and causes of autistic disorders. The functional variability of the brain functioning at different stages of the disease is observed. Theta rhythm (long-lasting and correlating with regression periods) dominates in the EEG picture of autistic disorders in Fragile X syndrome, Rett syndrome and atypical childhood psychosis. This fact makes it possible to assume that the pattern is peculiar to severe autistic disorders. In case of mild autism spectrum disorders or during remission, the beta-rhythm index and the sensorimotor rhythm increase. The alpha rhythm is often abnormal and falls off the age norms in frequency characteristics. Alpha rhythm indicates a favorable prognosis for patients with autism spectrum disorders. The functional variability of the brain functioning at different disease stages was observed. Keywords: autism spectrum disorders, autism, EEG, Kanner's syndrome, Asperger's syndrome, Rett syndrome, infantile psychosis, atypical autism, mirror neurons, mu rhythm. Расстройства аутистического спектра в настоящее время занимают все большую нишу в структуре детских заболеваний и, по мнению некоторых специалистов, принимают масштабы эпидемии. В отличие от многих других известных расстройств расстройства аутистического спектра не имеют четкого единого механизма ни на клеточном, ни на молекулярном, ни на структурном уровнях. В настоящее время имеется большое количество работ, посвященных данной теме, но ученые так и не пришли к единому мнению об истинной причине. Несмотря на схожую клиническую картину этиопатогенетические механизмы развития данных расстройств могут быть различными: от явлений дизонтогенеза и генетических мутаций до влияния экзогенных факторов. В данной статье представлены ЭЭГ-паттерны при различных фенотипах и причинах возникновения аутистических расстройств. Прослежена функциональная изменчивость работы мозга в различные стадии заболевания. В ЭЭГ-картине аутистических нарушений при синдроме Мартна – Белла, синдроме Ретта и атипичном детском психозе преобладает тета-ритм, как длительно, так и во взаимосвязи с периодами регресса, что дает возможность предполагать, что данный паттерн присущ тяжелым аутистическим расстройствам. При более легких расстройствах аутистического спектра или в периоды ремиссии увеличивается индекс бета-ритма, наблюдается нарастание сенсомоторного ритма. Альфа-ритм зачастую носит нерегулярный характер и несколько отстает по частотных характеристикам от возрастных норм. Наличие альфа-ритма свидетельствует о благоприятном прогнозе у пациентов с РАС. Прослежена функциональная изменчивость работы мозга в различные стадии заболевания. Ключевые слова: расстройства аутистического спектра, аутизм, ЭЭГ, синдром Каннера, синдром Аспергера, синдром Ретта, инфантильный психоз, атипичный аутизм, зеркальные нейроны, мю-ритм.

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

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Provvidenza M. Abruzzo ◽  
Alessandro Ghezzo ◽  
Alessandra Bolotta ◽  
Carla Ferreri ◽  
Renato Minguzzi ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Receiver Operating Characteristic ◽  
Biological Markers ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Metabolic Diseases ◽  
Autism Spectrum ◽  
Published Data ◽  
Spectrum Disorders ◽  
Receiver Operating

Autism Spectrum Disorders (ASD) are a heterogeneous group of neurodevelopmental disorders. Recognized causes of ASD include genetic factors, metabolic diseases, toxic and environmental factors, and a combination of these. Available tests fail to recognize genetic abnormalities in about 70% of ASD children, where diagnosis is solely based on behavioral signs and symptoms, which are difficult to evaluate in very young children. Although it is advisable that specific psychotherapeutic and pedagogic interventions are initiated as early as possible, early diagnosis is hampered by the lack of nongenetic specific biological markers. In the past ten years, the scientific literature has reported dozens of neurophysiological and biochemical alterations in ASD children; however no real biomarker has emerged. Such literature is here reviewed in the light of Receiver Operating Characteristic (ROC) analysis, a very valuable statistical tool, which evaluates the sensitivity and the specificity of biomarkers to be used in diagnostic decision making. We also apply ROC analysis to some of our previously published data and discuss the increased diagnostic value of combining more variables in one ROC curve analysis. We also discuss the use of biomarkers as a tool for advancing our understanding of nonsyndromic ASD.

Rett Syndrome

2017 ◽  
Author(s):  
C. L. Smith-Hicks ◽  
S. Naidu
Keyword(s):  
Autism Spectrum Disorders ◽  
Rett Syndrome ◽  
Clinical Phenotype ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Mecp2 Gene ◽  
Spectrum Disorders ◽  
Andreas Rett

Rett Syndrome (RTT) is a neurodevelopmental disorder that predominantly affects females but males with RTT have been identified. RTT was first described by an Austrian pediatrician, Andreas Rett. Rett syndrome was mapped to chromosome Xq28 in 1998 and a year later it was determined to be due to mutations in the MeCP2 gene at this locus. Identification of the gene led to the broadening of the clinical phenotype and further characterization into classic and atypical forms of the disease that overlap with Autism spectrum disorders during the period of regression. More than 95% of individuals with classic RTT have mutations in the MeCP2 gene.

The strengths and difficulties questionnaire (SDQ) in autism spectrum disorders

2017 ◽  
Vol 16 (3) ◽  
Author(s):  
Kamran Ali Salayev ◽  
Bjarte Sanne
Keyword(s):  
Autism Spectrum Disorders ◽  
Prosocial Behavior ◽  
Roc Analysis ◽  
Community Sample ◽  
Externalizing Disorders ◽  
Autism Spectrum ◽  
Scoring Methods ◽  
Emotional Symptoms ◽  
Strengths And Difficulties ◽  
Spectrum Disorders

AbstractObjective:To investigate the effectiveness of the strengths and difficulties questionnaire (SDQ) in the screening for autism spectrum disorders (ASD) and to find optimal scoring methods.Methods:The SDQ were given to parents of 4–12-year-old children with ASD (n=67), internalizing (n=49), externalizing disorders (n=87), and to a community sample (n=114). The total difficulties score and five subscales scores were compared between the four groups. Two additional scoring methods were calculated: prosocial behavior score minus peer relation problems score and sum of prosocial behavior score and emotional symptoms score. Receiving operating characteristics (ROC) analysis was used to find an effective way of screening for ASD.Results:All five subscales of the SDQ differed significantly between the ASD and the community samples. Only prosocial behavior and emotional symptoms subscales scores in the ASD group differed significantly from both internalizing and externalizing disorders groups (p<0.001). The total difficulties score reliably differentiated the ASD group from the community sample, but not from children with psychiatric disorders. Additional scoring methods’ problems showed the best area under the curve (AUC) in ROC analysis.Conclusion:The SDQ discriminates those with ASD well from other children with and without psychiatric disorders. Applying of additional algorithms is more effective rather than using the total difficulties or subscales scores alone.

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