Evidence map›Paper›PMID 33173195›Full record

ArticleMolecular psychiatry2021

Predicting the course of ADHD symptoms through the integration of childhood genomic, neural, and cognitive features.

Gustavo Sudre, Wendy Sharp, Paul Kundzicz, Marine Bouyssi-Kobar, Luke Norman, Saadia Choudhury, Philip Shaw

Abstract read
In one paragraph

Article in Molecular psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023
    Article
  8. Article
  9. Article
  10. Review
  11. 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

7 authors.

Gustavo SudreNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.
Wendy SharpOffice of the Clinical Director, National Institute of Mental Health, Bethesda, MD, USA.
Paul KundziczNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.ORCID http://orcid.org/0000-0002-6309-8960
Marine Bouyssi-KobarNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.
Luke NormanNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.
Saadia ChoudhuryNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.
Philip ShawNeurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA. shawp@mail.nih.gov.ORCID http://orcid.org/0000-0002-1313-2526

Funding

The neurobehavioral, environmental and genetic factors impacting ADHD.ZIAHG200378 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI SHAW, PHILIP · 2012 to 2025
$17.7M
Intramural NIH HHS Z99 MH999999
6 · The paper itself

Abstract

Childhood attention deficit hyperactivity disorder (ADHD) shows a highly variable course with age: some individuals show improving, others stable or worsening symptoms. The ability to predict symptom course could help individualize treatment and guide interventions. By studying a cohort of 362 youth, we ask if polygenic risk for ADHD, combined with baseline neural and cognitive features could aid in the prediction of the course of symptoms over an average period of 4.8 years. Compared to a never-affected comparison group, we find that participants with worsening symptoms carried the highest polygenic risk for ADHD, followed by those with stable symptoms, then those whose symptoms improved. Participants with worsening symptoms also showed atypical baseline cognition. Atypical microstructure of the cingulum bundle and anterior thalamic radiation was associated with improving symptoms while reduction of thalamic volume was found in those with stable symptoms. Machine-learning algorithms, trained and tested on independent groups, performed well in classifying those never affected against groups with worsening, stable, and improving symptoms (area under the curve >0.79). We conclude that some measures of polygenic risk, cognition, and neuroimaging show significant associations with the future course of ADHD symptoms and may have modest predictive power. These features warrant further exploration as prognostic tools.

Indexed as

Attention Deficit Disorder with HyperactivityWhite MatterAdolescentCognitionGenomicsHumansMultifactorial Inheritance

Identifiers

PMID33173195
PMCPMC8345321

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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.