Evidence map›Paper›PMID 32095160›Full record

ArticleInternational journal of computational biology and drug design2020

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes.

Jingwen Yan, Vinesh Raja V, Zhi Huang, Enrico Amico, Kwangsik Nho, Shiaofeng Fang, Olaf Sporns, Yu-Chien Wu, Andrew Saykin, Joaquin Goni and 2 more

Abstract read
In one paragraph

Article in International journal of computational biology and drug design, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Gene-Modulated Network Diffusion for Improved Modeling of Amyloid-bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Characterizing Amyloid Pathogenic Spread in Alzheimer's Disease Through A Network Diffusion Model.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025
    Article
  5. Caudal and Thalamic Segregation in White Matter Brain Network Communities in Alzheimer's Disease Population.... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics · 2024
    Article
  6. The ABC's of Alzheimer risk gene ABCA7.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
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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

12 authors.

Jingwen YanDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, 719 Indiana Ave, Indianapolis, USA.
Vinesh Raja VDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, 719 Indiana Ave, Indianapolis, USA.
Zhi HuangElectrical and Computing Engineering, Indiana University Purdue University Indianapolis, 46202 Indianapolis, USA.
Enrico AmicoIndustrial Engineering, Purdue University, 47096 West Lafayette, USA.
Kwangsik NhoRadiology and Imaging Sciences, Indiana University School of Medicine, 46202 Indianapolis, USA.
Shiaofeng FangComputer Science, Indiana University Purdue University Indianapolis, 46202 Indianapolis, USA.
Olaf SpornsPsychological and Brain Sciences, Indiana University, 47405 Bloomington, USA.
Yu-Chien WuRadiology and Imaging Sciences, Indiana University School of Medicine, 46202 Indianapolis, USA.
Andrew SaykinRadiology and Imaging Sciences, Indiana University School of Medicine, 46202 Indianapolis, USA.
Joaquin GoniIndustrial Engineering, Purdue University, 47096 West Lafayette, USA.
Li ShenBiostatistics, Epidemiology and Informatics, University of Pennsylvania, 19104 Philadelphia, USA.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Research Education ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI GHETTI, BERNARDINO FRANCESCO · 1991 to 2020
$37.3M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Memory Circuitry in MCI and Early Alzheimer’s Disease Prodrome: Molecular DriversR01AG019771 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 2001 to 2021
$6.9M
Modeling Axonal Density and Inflammation-Associated Cellularity in Alzheimer’s Disease Using Hybrid Diffusion ImagingR01AG053993 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI WU, YU-CHIEN · 2016 to 2020
$2.0M
Statistical models for multi-modal brain imaging studies of HIV-associated cognitive declineR01MH108467 · NIMH · INDIANA UNIVERSITY INDIANAPOLIS · PI HAREZLAK, JAROSLAW · 2015 to 2019
$2.0M
Integrative Bioinformatics Approaches to Human Brain Genomics and ConnectomicsR01EB022574 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI SHEN, LI · 2016 to 2019
$1.9M
Integrating Neuroimaging, Multi-omics, and Clinical Data in Complex DiseaseR01LM012535 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI NHO, KWANGSIK TIMOTHY · 2017 to 2021
$1.7M
Bioinformatics Strategies for Multidimensional Brain Imaging GeneticsR01LM011360 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI MOORE, JASON H., SAYKIN, ANDREW J · 2012 to 2015
$1.4M
Sensory and Perceptual Measures as Biomarkers of Alzheimer's Disease PathologyK01AG049050 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI RISACHER, SHANNON L · 2015 to 2019
$612k
NCATS NIH HHS UL1 TR001108NIA NIH HHS K01 AG049050NIA NIH HHS P30 AG010133NIA NIH HHS R01 AG019771NIA NIH HHS R01 AG053993NIBIB NIH HHS R01 EB022574NIMH NIH HHS R01 MH108467NLM NIH HHS R01 LM011360NLM NIH HHS R01 LM012535
6 · The paper itself

Abstract

backgroundAlzheimer's disease is the most common form of brain dementia characterized by gradual loss of memory followed by further deterioration of other cognitive function. Large-scale genome-wide association studies have identified and validated more than 20 AD risk genes. However, how these genes are related to the brain-wide breakdown of structural connectivity in AD patients remains unknown.

methodsWe used the genotype and DTI data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. After constructing the brain network for each subject, we extracted three types of link measures, including fiber anisotropy, fiber length and density. We then performed a targeted genetic association analysis of brain-wide connectivity measures using general linear regression models. Age at scan and gender were included in the regression model as covariates. For fair comparison of the genetic effect on different measures, fiber anisotropy, fiber length and density were all normalized with mean as 0 and standard deviation as one.We aim to discover the abnormal brain-wide network alterations under the control of 34 AD risk SNPs identified in previous large-scale genome-wide association studies.

resultsAfter enforcing the stringent Bonferroni correction, rs10498633 in

Indexed as

Alzheimer’s diseasebrain connectivityimaging genetics association

Identifiers

PMID32095160
PMCPMC7039398

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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.