Childhood ADHD, Going Beyond the Brain: A Meta-Analysis on Peripheral Physiological Markers of the Heart and the Gut

Payen, A.; Chen, Michelle J.; Carter, T. Grace; Kilmer, Ryan P.; Bennett, Jeanette M.

doi:10.3389/fendo.2022.738065

Cited by 10 publications

(6 citation statements)

References 101 publications

(257 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the AMSTAR-2 criteria, 21 SRs [7,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] scored "critically low," 16 SR [13,[37][38][39][40][41][42][43][44][45][46][47][48][49][50][51] scored "low," and 5 SR [36,[52][53][54][55] scored "moderate" (Figure 2). The most frequent drawbacks were as follows: no mentioning of the protocol in the systematic overview, no description of the rationale for the study designs included in the review, and no statement of funding for the included studies.…”

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

“…Alzheimer's disease (AD) [31,40,41], 10 SRs included attention deficit hyperactivity disorder (ADHD) [17,19,22,37,39,45,46,49,51,53], 1 SR included amyotrophic lateral sclerosis (ALS) [21], 2 SRs included anorexia nervosa (AN) [36,45], 5 SRs included bipolar disorder (BD) [20,43,45,46,52], 1 SR included eating disorder (ED) [27], 2 SRs included generalized anxiety disorder (GAD) [45,46], 9 SRs included major depressive disorder (MDD) [20,23,26,28,33,45,46,52,56], 3 SRs included multiple sclerosis (MS) [13,25,54], 1 SR included obsessive compulsive disorder (OCD) [45], 6 SRs included Parkinson's disease (PD) [7,25,27,35,44,47], 2 SRs included posttraumatic stress disorder (PTSD) [45,46], 2 SRs included spinal cord Injury (SCI) [13,…”

Section: Mediators Of Inflammationmentioning

confidence: 99%

See 1 more Smart Citation

The Role of Gut Microbiota in Various Neurological and Psychiatric Disorders—An Evidence Mapping Based on Quantified Evidence

Zang

Lai

et al. 2023

Mediators of Inflammation

View full text Add to dashboard Cite

Background and Object. There is a growing body of evidence highlighting the significant role of gut microbiota in various neurological and psychiatric disorders. We performed an evidence mapping to review the association between different microbiota and these disorders and assessed the strength of evidence for these associations. Methods. We searched PubMed, Cochrane Library, and Epistemonikos to identify systematic reviews and meta-analysis (SRs). We searched for neurological diseases and psychiatric disorders, including Alzheimer’s disease (AD), attention deficit hyperactivity disorder (ADHD), amyotrophic lateral sclerosis (ALS), autism spectrum disorder (ASD), anorexia nervosa (AN), bipolar disorder (BD), eating disorder (ED), generalized anxiety disorder (GAD), major depressive disorder (MDD), multiple sclerosis (MS), obsessive compulsive disorder (OCD), Parkinson’s disease (PD), posttraumatic stress disorder (PTSD), spinal cord injury (SCI), schizophrenia, and stroke. We used A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) to evaluate the quality of included SRs. We also created an evidence map showing the role of gut microbiota in neurological diseases and the certainty of the evidence. Results. In total, 42 studies were included in this evidence mapping. Most findings were obtained from observational studies. According to the AMSTAR-2 assessment, 21 SRs scored “critically low” in terms of methodological quality, 16 SR scored “low,” and 5 SR scored “moderate.” A total of 15 diseases have been investigated for the potential association between gut microbiome alpha diversity and disease, with the Shannon index and Simpson index being the most widely studied. A total of 12 diseases were investigated for potential link between beta diversity and disease. At the phylum level, Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, and Verrucomicrobia were more researched. At the genus level, Prevotella, Coprococcus, Parabacteroides, Phascolarctobacterium, Escherichia Shigella, Alistipes, Sutteralla, Veillonella, Odoribacter, Faecalibacterium, Bacteroides, Bifidobacterium, Dialister, and Blautia were more researched. Some diseases have been found to have specific flora changes, and some diseases have been found to have common intestinal microbiological changes. Conclusion. We found varied levels of evidence for the associations between gut microbiota and neurological diseases; some gut microbiota increased the risk of neurological diseases, whereas others showed evidence of benefit that gut microbiota might be promising therapeutic targets for such diseases.

show abstract

Section: Methodological Quality Of Included Studiesmentioning

confidence: 99%

Section: Mediators Of Inflammationmentioning

confidence: 99%

The Role of Gut Microbiota in Various Neurological and Psychiatric Disorders—An Evidence Mapping Based on Quantified Evidence

Zang

Lai

et al. 2023

Mediators of Inflammation

View full text Add to dashboard Cite

show abstract

“…Like other neuropsychiatric illnesses, ADHD has high comorbidity with gastrointestinal disturbances, such as constipation and abdominal pain (331,332), and diseases, such as ulcerative colitis (333). Some works have also reported discrepancies between ADHD and HC in the microbiome variability (334)(335)(336), which could be associated with distinct proinflammatory profiles and ADHD symptoms (337,338), although results are still inconclusive (339).…”

Section: Inflammation Emotion Dysregulation and Gut-brain Axis Abnorm...mentioning

confidence: 99%

Inflammation and emotional regulation: a narrative review of evidence and mechanisms in emotional dysregulation disorders

Petruso¹,

Giff²,

Milano³

et al. 2023

Preprint

View full text Add to dashboard Cite

Emotion dysregulation (ED) describes a difficulty with the modulation of which emotions are felt, as well as when and how these emotions are experienced or expressed. It is a focal overarching symptom in many severe and prevalent neuropsychiatric diseases, including bipolar disorders (BD), attention deficit and hyperactivity disorder (ADHD), and borderline personality disorder (BPD). In all these disorders, ED can manifest through symptoms of depression, anxiety, or affective lability. Considering the many similarities in symptoms between BD, ADHD, and BPD, a transdiagnostic approach is a promising lens of investigation. Mounting evidence supports the role of peripheral inflammatory markers and stress in the multifactorial aetiology and physiopathology of BD, ADHD, and BPD. Of note, neural circuits that regulate emotions appear particularly vulnerable to inflammatory insults and peripheral inflammation, which can impact the neuroimmune milieu of the central nervous system. Thus far, few studies have examined the link between ED and inflammation in BD, ADHD, and BPD. To our knowledge, no specific work has provided a critical comparison of the results from these disorders. To fill this gap in the literature, we review the known associations and mechanisms linking ED and inflammation in general, and clinically, in BD, ADHD, and BD. Our narrative review begins with an examination of the routes linking ED and inflammation, followed by a discussion of disorder-specific results accounting for methodological limitations and relevant confounding factors. Finally, we critically discuss both correspondences and discrepancies in the results and comment on potential vulnerability markers and promising therapeutic interventions.

show abstract

“…Although P300 event-related potentials are promising electroencephalography signatures that can objectively discriminate individuals with ADHD, it is not formally used for screening or diagnostic purposes due to its need for sophisticated equipment ( 6 , 7 ). Other physiological differences have been reported on the markers within the heart–brain and gut–brain axes as well as motor cortex physiology; however, these remain correlative measures and are unable to provide diagnostic confirmation ( 8 , 9 ). Given the complex etiology of ADHD and the common occurrence of multiple comorbidities, it is therefore challenging to identify children with ADHD by the present procedures, which are based on subjective assessments.…”

Section: Introductionmentioning

confidence: 99%

Utilizing artificial intelligence-based eye tracking technology for screening ADHD symptoms in children

Chen,

Wang,

Yang

et al. 2023

Front. Psychiatry

View full text Add to dashboard Cite

ObjectiveTo explore the potential of using artificial intelligence (AI)-based eye tracking technology on a tablet for screening Attention-deficit/hyperactivity disorder (ADHD) symptoms in children.MethodsWe recruited 112 children diagnosed with ADHD (ADHD group; mean age: 9.40 ± 1.70 years old) and 325 typically developing children (TD group; mean age: 9.45 ± 1.59 years old). We designed a data-driven end-to-end convolutional neural network appearance-based model to predict eye gaze to permit eye-tracking under low resolution and sampling rates. The participants then completed the eye tracking task on a tablet, which consisted of a simple fixation task as well as 14 prosaccade (looking toward target) and 14 antisaccade (looking away from target) trials, measuring attention and inhibition, respectively.ResultsTwo-way MANOVA analyses demonstrated that diagnosis and age had significant effects on performance on the fixation task [diagnosis: F(2, 432) = 8.231, ***p < 0.001; Wilks’ Λ = 0.963; age: F(2, 432) = 3.999, *p < 0.019; Wilks’ Λ = 0.982], prosaccade task [age: F(16, 418) = 3.847, ***p < 0.001; Wilks’ Λ = 0.872], and antisaccade task [diagnosis: F(16, 418) = 1.738, *p = 0.038; Wilks’ Λ = 0.938; age: F(16, 418) = 4.508, ***p < 0.001; Wilks’ Λ = 0.853]. Correlational analyses revealed that participants with higher SNAP-IV score were more likely to have shorter fixation duration and more fixation intervals (r = −0.160, 95% CI [0.250, 0.067], ***p < 0.001), poorer scores on adjusted prosaccade accuracy, and poorer scores on antisaccade accuracy (Accuracy: r = −0.105, 95% CI [−0.197, −0.011], *p = 0.029; Adjusted accuracy: r = −0.108, 95% CI [−0.200, −0.015], *p = 0.024).ConclusionOur AI-based eye tracking technology implemented on a tablet could reliably discriminate eye movements of the TD group and the ADHD group, providing a potential solution for ADHD screening outside of clinical settings.

show abstract

Childhood ADHD, Going Beyond the Brain: A Meta-Analysis on Peripheral Physiological Markers of the Heart and the Gut

Cited by 10 publications

References 101 publications

The Role of Gut Microbiota in Various Neurological and Psychiatric Disorders—An Evidence Mapping Based on Quantified Evidence

The Role of Gut Microbiota in Various Neurological and Psychiatric Disorders—An Evidence Mapping Based on Quantified Evidence

Inflammation and emotional regulation: a narrative review of evidence and mechanisms in emotional dysregulation disorders

Utilizing artificial intelligence-based eye tracking technology for screening ADHD symptoms in children

Contact Info

Product

Resources

About