Evidence map›Paper›PMID 36987996›Full record

ArticleHuman brain mapping2023

General dimensions of human brain morphometry inferred from genome-wide association data.

Anna E Fürtjes, Ryan Arathimos, Jonathan R I Coleman, James H Cole, Simon R Cox, Ian J Deary, Javier de la Fuente, James W Madole, Elliot M Tucker-Drob, Stuart J Ritchie

Abstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–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

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

  1. Pooled it
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  6. Causal relationships between neuroimaging phenotypes and the risk of early and late-onset alzheimer's disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Article
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  18. Structural MRI of brain similarity networks.Nature reviews. Neuroscience · 2025
    Review
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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

10 authors.

Anna E FürtjesSocial, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.ORCID 0000-0001-6590-4957
Ryan ArathimosSocial, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
Jonathan R I ColemanSocial, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
James H ColeDepartment of Neuroimageing, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.ORCID 0000-0003-1908-5588
Simon R CoxDepartment of Psychology, The University of Edinburgh, Edinburgh, EH8 9JZ, UK.ORCID 0000-0003-4036-3642
Ian J DearyDepartment of Psychology, The University of Edinburgh, Edinburgh, EH8 9JZ, UK.
Javier de la FuenteDepartment of Psychology, University of Texas at Austin, Austin, Texas, 78712-1043, USA.
James W MadoleDepartment of Psychology, University of Texas at Austin, Austin, Texas, 78712-1043, USA.
Elliot M Tucker-DrobDepartment of Psychology, University of Texas at Austin, Austin, Texas, 78712-1043, USA.
Stuart J RitchieSocial, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.

Funding

Program Development and Pilot CoreP30AG066614 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI DEBRA J. UMBERSON · 2020 to 2026
$5.2M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI Elizabeth T. Gershoff · 2017 to 2026
$5.2M
Evaluating Longitudinal Changes in the Human Structural Connectome in Relation to Cognitive AgingR01AG054628 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2017 to 2021
$2.7M
Large-Scale Genomic Analysis of Aging-Related Cognitive Change Prior to Dementia OnsetRF1AG073593 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2021 to 2021
$2.1M
Medical Research Council 221890/Z/20/ZMedical Research Council MR/R024065/1Medical Research Council MR/R024790/1Medical Research Council MR/R024790/2NIA NIH HHS P30 AG066614NIA NIH HHS R01 AG054628NIA NIH HHS RF1 AG073593NICHD NIH HHS P2C HD042849Wellcome Trust
6 · The paper itself

Abstract

Understanding the neurodegenerative mechanisms underlying cognitive decline in the general population may facilitate early detection of adverse health outcomes in late life. This study investigates genetic links between brain morphometry, ageing and cognitive ability. We develop Genomic Principal Components Analysis (Genomic PCA) to model general dimensions of brain-wide morphometry at the level of their underlying genetic architecture. Genomic PCA is applied to genome-wide association data for 83 brain-wide volumes (36,778 UK Biobank participants) and we extract genomic principal components (PCs) to capture global dimensions of genetic covariance across brain regions (unlike ancestral PCs that index genetic similarity between participants). Using linkage disequilibrium score regression, we estimate genetic overlap between those general brain dimensions and cognitive ageing. The first genetic PCs underlying the morphometric organisation of 83 brain-wide regions accounted for substantial genetic variance (R

Indexed as

Cognitive DysfunctionGenome-Wide Association StudyAgingBrainCognitionHumansPolymorphism, Single Nucleotidebrain agecognitive abilitycomplex traitsgeneticsstatistical modellingstructural brain networksstructural neuroimageing

Identifiers

PMID36987996
PMCPMC10171533

What OpenQuestion holds

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LicenceCC BY
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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.