Evidence map›Paper›PMID 39145420›Full record

ArticleCNS neuroscience & therapeutics2024

Interference of default mode on attention networks in adults with attention-deficit/hyperactivity disorder and its association with genetic variants and treatment outcomes.

Lu Liu, Di Chen, Fang Huang, Tianye Jia, Wei Cheng, Meirong Pan, Mengjie Zhao, Xuan Bu, Xuhong Liao, Yufeng Wang and 3 more

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
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

13 authors.

Lu LiuPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.ORCID 0000-0003-0194-1454
Di ChenInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Fang HuangPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.
Tianye JiaInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Wei ChengInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Meirong PanPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.
Mengjie ZhaoPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.
Xuan BuState Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Xuhong LiaoSchool of Systems Science, Beijing Normal University, Beijing, China.
Yufeng WangPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.
Miao CaoInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Qiujin QianPeking University Sixth Hospital/Institute of Mental Health, Beijing, China.
Jianfeng FengInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Funding

Beijing Nova Program 20220484061Beijing Nova Program 20230484444Capital's Funds for Health Improvement and Research CFH: 2020-2-4112Capital's Funds for Health Improvement and Research CFH: 2024-2-4114Clinical Medicine Plus X-Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities PKU2023LCXQ043National Key Basic Research Program of China 973 program 2014CB846104National Natural Science Foundation of China 61932008National Natural Science Foundation of China 81571340National Natural Science Foundation of China 81901826National Natural Science Foundation of China 82271575Natural Science Foundation of Shanghai 19ZR1405600Natural Science Foundation of Shanghai 20ZR1404900Shanghai Municipal Science and Technology Major Project 2018SHZDZX01ZJLab and Shanghai Center for Brain Science and Brain-inspired Technology
6 · The paper itself

Abstract

aimsAltered brain functional connectivity has been proposed as the neurobiological underpinnings of attention-deficit/hyperactivity disorder (ADHD), and the default mode interference hypothesis is one of the most popular neuropsychological models. Here, we explored whether this hypothesis is supported in adults with ADHD and the association with high-risk genetic variants and treatment outcomes.

methodsVoxel-based whole-brain connectome analysis was conducted on resting-state functional MRI data from 84 adults with ADHD and 89 healthy controls to identify functional connectivity substrates corresponding to ADHD-related alterations. The candidate genetic variants and 12-week cognitive behavioral therapy data were leveraged from the same population to assess these associations.

resultsWe detected breakdowns of functional connectivity in the precuneus and left middle temporal gyrus in adults with ADHD, with exact contributions from decreased connectivity within the default mode, dorsal and ventral attention networks, as well as increased connectivity among them with the middle temporal gyrus serving as a crucial 'bridge'. Additionally, significant associations between the altered functional connectivity and genetic variants in both MAOA and MAOB were detected. Treatment restored brain function, with the amelioration of connectivity of the middle temporal gyrus, accompanied by improvements in ADHD core symptoms.

conclusionsThese findings support the interference of default mode on attention in adults with ADHD and its association with genetic risk variants and clinical management, providing insights into the underlying pathogenesis of ADHD and potential biomarkers for treatment evaluation.

Indexed as

Attention Deficit Disorder with HyperactivityConnectomeDefault Mode NetworkMagnetic Resonance ImagingAdultAttentionBrainCognitive Behavioral TherapyFemaleGenetic VariationHumansMaleNerve NetTreatment OutcomeYoung Adultadults with ADHDcognitive behavioral therapyconnectome analysisfunctional connectivityMAO genotype

Identifiers

PMID39145420
PMCPMC11325164

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.