Evidence map›Paper›PMID 34511130›Full record

ArticleTranslational neurodegeneration2021

Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis.

Wenbin Li, Qianqian Wei, Yanbing Hou, Du Lei, Yuan Ai, Kun Qin, Jing Yang, Graham J Kemp, Huifang Shang, Qiyong Gong

Open access · goldAbstract read
In one paragraph

Article in Translational neurodegeneration, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Potential Roles of Neuroimaging in Motor Neuron Disease.Current neurology and neuroscience reports · 2026
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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 at 4 institutions in 3 countries.

Wenbin Li *Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
Qianqian Wei *Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China.
Yanbing HouLaboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China.
Du LeiDepartment of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA.
Yuan AiHuaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
Kun QinHuaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
Jing YangHuaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
Graham J KempDepartment of Musculoskeletal and Ageing Science and MRC - Versus Arthritis Centre for Integrated Research Into Musculoskeletal Ageing, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK.
Huifang ShangLaboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China. hfshang2002@163.com.
Qiyong GongHuaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China. qiyonggong@hmrrc.org.cn.ORCID 0000-0002-5912-4871
Sichuan University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNUniversity of Cincinnati Medical Center · USUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThere is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.

methodsMagnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.

resultsCompared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient C

conclusionDisruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.

Indexed as

Disease ProgressionAdultAmyotrophic Lateral SclerosisDiffusion Magnetic Resonance ImagingFemaleHumansMachine LearningMaleMiddle AgedNerve NetWhite MatterAmyotrophic lateral sclerosisConnectomicsDTIMachine learningNetworkPsychoradiologyWhite matter

Identifiers

PMID34511130
PMCPMC8436442
OpenAlexW3199144798

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.