Evidence map›Paper›PMID 31176952›Full record

ArticleNeuroImage. Clinical2019

Brain function, structure and genomic data are linked but show different sensitivity to duration of illness and disease stage in schizophrenia.

Na Luo, Lin Tian, Vince D Calhoun, Jiayu Chen, Dongdong Lin, Victor M Vergara, Shuquan Rao, Jian Yang, Chuanjun Zhuo, Yong Xu and 3 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. [Illness duration-related developmental trajectory of progressive cerebral gray matter changes in schizophrenia].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
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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

13 authors at 8 institutions in 2 countries.

Na LuoBrainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Lin TianWuxi Mental Health Center, Wuxi 214000, China.
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA; The Mind Research Network, Albuquerque, NM 87106, USA.
Jiayu ChenTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA.
Dongdong LinTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA.
Victor M VergaraTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA.
Shuquan RaoSchool of Life Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Jian YangBeijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China.
Chuanjun ZhuoDepartment of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory (PNGC-Lab), Tianjin Mental Health Center, Nankai University Affiliated Anding Hospital, Tianjin 300222, China.
Yong XuDepartment of Psychiatry, First Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan 030000, China.
Jessica A TurnerDepartment of Psychology, Neuroscience Institute, Georgia State University, Atlanta, GA, USA.
Fuquan ZhangWuxi Mental Health Center, Wuxi 214000, China. Electronic address: zhangfq@njmu.edu.cn.
Jing SuiBrainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: kittysj@gmail.com.
Georgia Institute of Technology · USChinese Academy of Sciences · CNJiangxi Mental Health Center · CNBeijing Institute of Technology · CNGeorgia State University · USNankai University · CNShanxi Medical University · CNSouthwest Jiaotong University · CN

Funding

Data-driven approaches to identify biomarkers from multimodal imaging big dataR01MH117107 · NIMH · GEORGIA STATE UNIVERSITY · PI CALHOUN, VINCE D · 2019 to 2022
$1.6M
Data-driven approaches to identify biomarkers from multimodal imaging big dataR56MH117107 · NIMH · THE MIND RESEARCH NETWORK · PI SUI, JING · 2018 to 2018
$453k
NIMH NIH HHS R01 MH117107NIMH NIH HHS R56 MH117107
6 · The paper itself

Abstract

The progress of schizophrenia at various stages is an intriguing question, which has been explored to some degree using single-modality brain imaging data, e.g. gray matter (GM) or functional connectivity (FC). However it remains unclear how those changes from different modalities are correlated with each other and if the sensitivity to duration of illness and disease stages across modalities is different. In this work, we jointly analyzed FC, GM volume and single nucleotide polymorphisms (SNPs) data of 159 individuals including healthy controls (HC), drug-naïve first-episode schizophrenia (FESZ) and chronic schizophrenia patients (CSZ), aiming to evaluate the links among SNP, FC and GM patterns, and their sensitivity to duration of illness and disease stages in schizophrenia. Our results suggested: 1) both GM and FC highlighted impairments in hippocampal, temporal gyrus and cerebellum in schizophrenia, which were significantly correlated with genes like SATB2, GABBR2, PDE4B, CACNA1C etc. 2) GM and FC presented gradually decrease trend (HC > FESZ>CSZ), while SNP indicated a non-gradual variation trend with un-significant group difference observed between FESZ and CSZ; 3) Group difference between HC and FESZ of FC was more remarkable than GM, and FC presented a stronger negative correlation with duration of illness than GM (p = 0.0006). Collectively, these results highlight the benefit of leveraging multimodal data and provide additional clues regarding the impact of mental illness at various disease stages.

Indexed as

ConnectomeDisease ProgressionGray MatterMagnetic Resonance ImagingSchizophreniaAdultFemaleHumansMaleMiddle AgedPolymorphism, Single NucleotideSensitivity and SpecificityTime FactorsYoung AdultDuration of illnessICAMultimodal fusionSchizophrenia stagesSensitivitySNP-FC-GM

Identifiers

PMID31176952
PMCPMC6558215
OpenAlexW2946994504

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.