Evidence map›Paper›PMID 35139813›Full record

ArticleBMC psychiatry2022

Transdiagnostic symptom subtypes across autism spectrum disorders and attention deficit hyperactivity disorder: validated by measures of neurocognition and structural connectivity.

Manxue Zhang, Yan Huang, Jian Jiao, Danfeng Yuan, Xiao Hu, Pingyuan Yang, Rui Zhang, Liangjian Wen, Mingjing Situ, Jia Cai and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 1 country.

Manxue Zhang *Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Yan Huang *Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Jian JiaoMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Danfeng YuanMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Xiao HuMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Pingyuan YangMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Rui ZhangUniversity of Electronic Science and Technology of China, Chengdu, China.
Liangjian WenUniversity of Electronic Science and Technology of China, Chengdu, China.
Mingjing SituMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Jia CaiMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Xueli SunMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Kuifang GuoMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Xia HuangMental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Yi HuangMental Health Center, West China Hospital of Sichuan University, Chengdu, China. huangyu@scu.edu.cn.
West China Hospital of Sichuan University · CNSichuan University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundsAutism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are neurodevelopmental disorders that exhibit within-disorder heterogeneity and cross-disorder phenotypic overlap, thus suggesting that the current disease categories may not fully represent the etiologic essence of the disorders, especially for highly comorbid neurodevelopmental disorders. In this study, we explored the subtypes of a combined sample of ASD and ADHD by integrating measurements of behavior, cognition and brain imaging.

methodsA total of 164 participants, including 65 with ASD, 47 with ADHD, and 52 controls, were recruited. Unsupervised machine learning with an agglomerative hierarchical clustering algorithm was used to identify transdiagnostic symptom clusters. Neurocognition and brain structural connectivity measurements were used to assess symptom clusters. Mediation analysis was used to explore the relationship between transdiagnostic symptoms, neurocognition and brain structural connectivity.

resultsWe identified three symptom clusters that did not fall within the diagnostic boundaries of DSM. External measurements from neurocognition and neuroimaging domains supported distinct profiles, including fine motor function, verbal fluency, and structural connectivity in the corpus callosum between these symptom clusters, highlighting possible biomarkers for ASD and ADHD. Additionally, fine motor function was shown to mediate the relationship between the corpus callosum and perseveration symptoms.

conclusionsIn this transdiagnostic study on ASD and ADHD, we identified three subtypes showing meaningful associations between symptoms, neurocognition and brain white matter structural connectivity. The fine motor function and structural connectivity of corpus callosum might be used as biomarkers for neurodevelopmental disorders with social skill symptoms. The results of this study highlighted the importance of precise phenotyping and further supported the effects of fine motor intervention on ASD and ADHD.

Indexed as

Attention Deficit Disorder with HyperactivityAutism Spectrum DisorderWhite MatterHumansNeuroimagingSyndromeAttention deficit hyperactivity disorderAutism Spectrum disorderDiffusion tensor imagingNeurocognitionTransdiagnostic

Identifiers

PMID35139813
PMCPMC8827180
OpenAlexW4210877148

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.