Evidence map›Paper›PMID 30255713›Full record

ArticleBrain connectivity2019

Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease.

Seong Jae Hwang, Nagesh Adluru, Won Hwa Kim, Sterling C Johnson, Barbara B Bendlin, Vikas Singh

Abstract read
In one paragraph

Article in Brain connectivity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging.Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence · 2019
    Article
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  7. Article
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

6 authors.

Seong Jae Hwang1 Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin.
Nagesh Adluru3 Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, Wisconsin.
Won Hwa Kim4 Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, Texas.
Sterling C Johnson2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.
Barbara B Bendlin2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.
Vikas Singh1 Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin.

Funding

Wisconsin Registry for Alzheimer's Prevention: Sex Differences in DNA MethylationR01AG027161 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Nathaniel Ark Chin, Sterling C Johnson · 2007 to 2026
$35.6M
Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
Wisconsin Alzheimer's Disease Research CenterP50AG033514 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI CHAPPELL, RICHARD J · 2009 to 2018
$16.2M
TrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3M
Waisman Intellectual and Developmental Disabilities Research Center Down Syndrome RegistryU54HD090256 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI POLLAK, SETH D · 2016 to 2020
$6.0M
Alzheimer's Disease Connectome ProjectUF1AG051216 · NIA · MEDICAL COLLEGE OF WISCONSIN · PI BENDLIN, BARBARA BRIGITTA, LI, SHI-JIANG · 2016 to 2019
$5.8M
White matter degeneration: biomarkers in preclinical Alzheimer's DiseaseR01AG037639 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI BENDLIN, BARBARA BRIGITTA · 2012 to 2023
$5.3M
SV2A PET imaging in Alzheimer's DiseaseR01AG062285 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI BENDLIN, BARBARA BRIGITTA, CHRISTIAN, BRADLEY T · 2018 to 2022
$5.3M
Algebraic Formulations for Characterizing Structural Brain Connectivity Changes and Pathology Transmission Networks in Preclinical Alzheimer's DiseaseRF1AG059312 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI BENDLIN, BARBARA BRIGITTA, SINGH, VIKAS · 2019 to 2019
$1.8M
Manifold-valued statistical models for longitudinal morphometic analysis in preclinical Alzheimer's disease (AD)R01EB022883 · NIBIB · UNIVERSITY OF WISCONSIN-MADISON · PI JOHNSON, STERLING C, SINGH, VIKAS · 2016 to 2018
$995k
White matter degeneration: biomarkers in preclinical Alzheimer's DiseaseR56AG037639 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI BENDLIN, BARBARA BRIGITTA · 2017 to 2017
$759k
NIAID NIH HHS U54 AI117924NIA NIH HHS P50 AG033514NIA NIH HHS R01 AG027161NIA NIH HHS R01 AG037639NIA NIH HHS R01 AG062285NIA NIH HHS R56 AG037639NIA NIH HHS RF1 AG059312NIA NIH HHS UF1 AG051216NIBIB NIH HHS R01 EB022883NICHD NIH HHS U54 HD090256NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

Characterizing Alzheimer's disease (AD) at pre-clinical stages is crucial for initiating early treatment strategies. It is widely accepted that amyloid accumulation is a primary pathological event in AD. Also, loss of connectivity between brain regions is suspected of contributing to cognitive decline, but studies that test these associations using either local (i.e., individual edges) or global (i.e., modularity) connectivity measures may be limited. In this study, we utilized data acquired from 139 cognitively unimpaired participants. Sixteen gray matter (GM) regions known to be affected by AD were selected for analysis. For each of the 16 regions, the effect of amyloid burden, measured using Pittsburgh Compound B (PiB) positron emission tomography, on each of the 1761 brain network connections derived from diffusion tensor imaging (DTI) connecting 162 GM regions, was investigated. Applying our unique multiresolution statistical analysis called the Wavelet Connectivity Signature (WaCS), this study demonstrates the relationship between amyloid burden and structural brain connectivity as assessed with DTI. Our statistical analysis using WaCS shows that in 15 of 16 GM regions, statistically significant relationships between amyloid burden in those regions and structural connectivity networks were observed. After applying multiple testing correction, 10 unique structural brain connections were found to be significantly associated with amyloid accumulation. For 7 of those 10 network connections, the decrease in their network connection strength indexed by fractional anisotropy was, in turn, associated with lower cognitive function, providing evidence that AD-related structural connectivity loss is a correlate of cognitive decline.

Indexed as

AgedAlzheimer DiseaseBrainBrain MappingCognitionCognitive DysfunctionConnectomeDiffusion Tensor ImagingFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological TestsPlaque, AmyloidPositron-Emission TomographyAlzheimer's diseaseamyloid pathologybrain connectivitypre-clinical AD

Identifiers

PMID30255713
PMCPMC6909755

What OpenQuestion holds

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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.