Evidence map›Paper›PMID 42092107›Full record

ArticleCommunications biology2026

Shared genetic architecture between the topology of brain white matter structural connectome and fluid intelligence.

Xinyi Dong, Weijie Huang, Hao-Jie Chen, Yunhao Zhang, Bing Liu, Daoqiang Zhang, Zhanjun Zhang, Guolin Ma, Ni Shu

Abstract read
In one paragraph

Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Xinyi Dong *State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0003-0068-5137
Weijie Huang *College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing, China. weijieh@nuaa.edu.cn.ORCID http://orcid.org/0000-0002-2481-1188
Hao-Jie ChenState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0002-4362-1056
Yunhao ZhangState Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Bing LiuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0003-2029-5187
Daoqiang ZhangCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing, China.ORCID http://orcid.org/0000-0002-5658-7643
Zhanjun ZhangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Guolin MaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, China.
Ni ShuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. nshu@bnu.edu.cn.ORCID http://orcid.org/0000-0003-2420-2910

Funding

National Natural Science Foundation of China (National Science Foundation of China) 210510238National Natural Science Foundation of China (National Science Foundation of China) 32271145National Natural Science Foundation of China (National Science Foundation of China) 81871425National Natural Science Foundation of China (National Science Foundation of China) 82301608Natural Science Foundation of Beijing Municipality (Beijing Natural Science Foundation) L252087
6 · The paper itself

Abstract

White matter (WM) connections support efficient interregional communication and form the structural basis of human fluid intelligence. However, the shared genetic architecture between WM structural connectome and fluid intelligence remains largely unknown. In this study, we analyzed diffusion-weighted MRI data from 26,655 UK Biobank participants to construct individual WM connectome and performed genome-wide association analyses on global and regional network topology. We identified 41 single nucleotide polymorphisms (SNPs) significantly associated with global efficiency and 45 SNPs linked to nodal efficiency. Genetic correlations with fluid intelligence were observed for 128 brain regions, with 44 and 3 regions sharing SNPs within chromosomes 6q21 and 3p21.1, respectively. Mendelian randomization revealed causal effects from WM connectome to fluid intelligence, particularly in the orbital and superior frontal gyrus. Finally, integrating polygenic scores with network efficiency improved the prediction of individual fluid intelligence. These findings highlight the genetic basis linking WM connectome topology and fluid intelligence, providing new insights into the neurogenetic underpinnings of fluid intelligence.

Indexed as

BrainConnectomeIntelligenceWhite MatterDiffusion Magnetic Resonance ImagingFemaleGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single Nucleotide

Identifiers

PMID42092107
PMCPMC13358041

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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.