scholarly journals In-Utero SSRI and SNRI Exposure and the Risk of Neurodevelopmental Disorders in Children: A Population-Based Retrospective Cohort Study Utilizing Linked Administrative Data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Deepa Singal ◽  
Dan Chateau ◽  
Matthew Dahl ◽  
Shelley Derksen ◽  
Chelsea Ruth ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Anxiety Disorder ◽  
Disease Severity ◽  
Administrative Data ◽  
Neurodevelopmental Disorders ◽  
Population Based ◽  
In Utero ◽  
Autism Spectrum ◽  
Hazard Ratio ◽  
Spectrum Disorder

IntroductionMany studies demonstrating an association between in utero exposure to serotonergic antidepressants and higher risk of neurodevelopmental disorders in children are confounded by history of maternal depression and disease severity. We conducted a population-based analysis of women diagnosed with mood/anxiety disorder, a patient population for whom pharmacotherapy is clearly indicated. Objectives and ApproachUsing linked population-based administrative data, we identified all mother-newborn pairs in Manitoba (born 1996 to 2009, with follow-up through 2014). High dimensional propensity scores and inverse probability treatment weighting were used to address confounding by indication and disease severity. The final trimmed cohort consisted of mothers who were diagnosed with a mood/anxiety disorder from 90 days prior to conception until delivery (n=4995). Cox Proportional Hazard Regression models were used to estimate risk of Autism Spectrum Disorder, epilepsy and attention deficit hyperactivity disorder (ADHD) in offspring. In addition to clinical data, we used novel education data to define outcomes in children. ResultsAmong the cohort of mothers diagnosed with a mood/anxiety disorder during pregnancy or up to 90 days before, 16.8% received at least two dispensations of an SSRI or SNRI during pregnancy. We did not observe an association between use of SSRIs/SNRIs during pregnancy and increased risk of Autism Spectrum Disorder (hazard ratio 0.92; 95% CI 0.42 to 2.03), epilepsy (hazard ratio 1.21; 95% CI 0.48 to 3.05), or ADHD (hazard ratio 1.13, 95% CI 0.78 to 1.64) among offspring. Conclusion/ImplicationsIn the absence of randomized control trials, large observation studies using sophisticated data analysis are the gold standard of evidence to help patients and clinicians making the decision to continue antidepressant use during pregnancy. Results of this study reassure women for whom the medication is clinically indicated.

The Relationship between Autism Spectrum Disorder and Tourette Syndrome in Childhood: An Overview of Shared Characteristics

2017 ◽  
Vol 15 (03) ◽  
pp. 115-122 ◽  
Author(s):  
Mariangela Gulisano ◽  
Carla Domini ◽  
Maria Ferro ◽  
Paolo Curatolo ◽  
Renata Rizzo
Keyword(s):  
Autism Spectrum Disorder ◽  
Tourette Syndrome ◽  
Neurodevelopmental Disorders ◽  
Population Based ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Similarities And Differences ◽  
High Degree ◽  
The Relationship ◽  
Degree Of Overlap

AbstractAutism spectrum disorder (ASD) and Tourette syndrome (TS) are neurodevelopmental disorders. ASD and TS are traditionally considered to be separate conditions. Nevertheless, these disorders have a high degree of overlap, and “pure” cases are rare in both clinical and population-based studies. The aim of the present review was to analyze the similarities and differences between ASD and TS on the basis of genetic and neuroradiological findings.

scholarly journals Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Data Exchange ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

scholarly journals Timing of Identification Among Children With an Autism Spectrum Disorder: Findings From a Population-Based Surveillance Study

2009 ◽  
Vol 48 (5) ◽  
pp. 474-483 ◽  
Author(s):  
Paul T. Shattuck ◽  
Maureen Durkin ◽  
Matthew Maenner ◽  
Craig Newschaffer ◽  
David S. Mandell ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Population Based ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Surveillance Study

Automatic Detection and Assessment of Autism Spectrum Disorder

2021 ◽  
pp. 396-425
Author(s):  
Thanga Aarthy M. ◽  
Menaka R. ◽  
Karthik R.
Keyword(s):  
Autism Spectrum Disorder ◽  
Early Detection ◽  
Early Diagnosis ◽  
Neurodevelopmental Disorders ◽  
Pathological Condition ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Attention Deficit Hyperactive Disorder ◽  
Clinical Methods

Children with neurodevelopmental disorders are increasing gradually every year. One in 100 children are diagnosed with brain function disorder. There are wide categories of disorder such as attention deficit hyperactive disorder, learning, autism spectrum disorder (ASD), etc. In this work, the focus is on ASD, its clinical methods, and analysis in various research works. ASD is a neurodevelopmental disorder which affects the intellectual functioning, social interaction (adaptive behavior), and has a specific obsessive interest. At present, there is no known cure for ASD, but the level of the pathological condition can be reduced when it is detected early. Early detection is tough and challenging till date. Many researches were carried out to ease the early detection for clinicians. Each method has its own merits and demerits. This chapter reviews and condenses various research works and their efficacy in analysis for the early diagnosis and improvement in children with autism.

scholarly journals Salivary Cytokine Profile as a Possible Predictor of Autism Spectrum Disorder

2020 ◽  
Vol 9 (10) ◽  
pp. 3101 ◽  
Author(s):  
Joanna Samborska-Mazur ◽  
Anna Kostiukow ◽  
Izabela Miechowicz ◽  
Dorota Sikorska ◽  
Rafał Rutkowski ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Neurodevelopmental Disorders ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Typically Developing ◽  
Monocyte Chemoattractant Protein 1 ◽  
Children With Asd ◽  
Cytokine Levels ◽  
Factor Α ◽  
Gait Disturbances

Autism spectrum disorder (ASD) is characterized by neurodevelopmental disorders and alterations in immune function and cytokine levels. The aim of this study is to determine the salivary levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor α (TNFα), monocyte chemoattractant protein-1 (MCP-1), Regulated on Activation, Normal T-cell Expressed and Secreted (RANTES), and Eotaxin in children with ASD and in healthy controlsto assess their predictive potential. We explored correlations between the cytokine levels and the neurodevelopmental disorders related to ASD. The study comprised 19 children with ASD and 19 typically developing (TD) ones. We analyzed salivary levels of IL-1β, IL-6, IL-8, TNFα, MCP-1, RANTES, and eotaxin on Luminex with custom-designed 7-plex kits. The level of RANTES in ASD children was significantly lower than those of TD. In TDs, the salivary levels of IL-1β, MCP-1, and TNFα correlated positively with age. In ASD, the cytokine levels did not correlate with age. There were statistically significant differences between the RANTES level and aggression and gait disturbances, between IL-8 level and fixations/stimulations, and between IL-1β level and no active speech. The levels of the cytokine detected can manifest both systemic and local changes related to ASD. The cytokine pattern cannot be used as a sole ASD predictor, but the salivary levels may be helpful in categorizing the ASD subtype.

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