Evidence map›Paper›PMID 25257986›Full record

ArticleNeurobiology of aging2015

Seemingly unrelated regression empowers detection of network failure in dementia.

Neda Jahanshad, Talia M Nir, Arthur W Toga, Clifford R Jack, Matt A Bernstein, Michael W Weiner, Paul M Thompson, Alzheimer's Disease Neuroimaging Initiative

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurobiology of aging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Overview of ADNI MRI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
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

8 authors.

Neda JahanshadImaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA.
Talia M NirImaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA.
Arthur W TogaImaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA.
Clifford R JackDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Matt A BernsteinDepartment of Radiology, University of California San Francisco, CA, USA.
Michael W WeinerDepartment of Radiology, University of California San Francisco, CA, USA; Department of Medicine, University of California San Francisco, CA, USA; Department of Psychiatry, University of California San Francisco, CA, USA; Department of Veterans Affairs Medical Center, San Francisco, CA, USA.
Paul M ThompsonImaging Genetics Center, Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA; Department of Neurology, University of Southern California, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA; Department of Radiology, University of Southern California, Los Angeles, CA, USA; Department of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Pediatrics, University of Southern California, Los Angeles, CA, USA; Department of Ophthalmology, University of Southern California, Los Angeles, CA, USA. Electronic address: pthomp@usc.edu.
Alzheimer's Disease Neuroimaging Initiative

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARANDA, MARIA P. · 1985 to 2019
$41.0M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
Training U54EB020403 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2018
$10.1M
Growth factors, neuroinflammation, exercise, and brain integrityRF1AG041915 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2014
$2.9M
HARDI Mapping of Disease Effects on the BrainR01EB008432 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI THOMPSON, PAUL M · 2009 to 2012
$2.6M
Alzheimer's disease risk analyzed using population imaging genomicsR01AG040060 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2011 to 2016
$2.5M
A Multidimensional Alzheimer's Disease Brain AtlasR01EB008281 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI THOMPSON, PAUL M · 2007 to 2010
$1.4M
NIA NIH HHS P50 AG005142NIA NIH HHS R01 AG040060NIA NIH HHS RF1 AG041915NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG024904NIBIB NIH HHS P41 EB015922NIBIB NIH HHS R01 EB008281NIBIB NIH HHS R01 EB008432NIBIB NIH HHS U54 EB020403
6 · The paper itself

Abstract

Brain connectivity is progressively disrupted in Alzheimer's disease (AD). Here, we used a seemingly unrelated regression (SUR) model to enhance the power to identify structural connections related to cognitive scores. We simultaneously solved regression equations with different predictors and used correlated errors among the equations to boost power for associations with brain networks. Connectivity maps were computed to represent the brain's fiber networks from diffusion-weighted magnetic resonance imaging scans of 200 subjects from the Alzheimer's Disease Neuroimaging Initiative. We first identified a pattern of brain connections related to clinical decline using standard regressions powered by this large sample size. As AD studies with a large number of diffusion tensor imaging scans are rare, it is important to detect effects in smaller samples using simultaneous regression modeling like SUR. Diagnosis of mild cognitive impairment or AD is well known to be associated with ApoE genotype and educational level. In a subsample with no apparent associations using the general linear model, power was boosted with our SUR model-combining genotype, educational level, and clinical diagnosis.

Indexed as

Neural ConductionAgedAged, 80 and overAlzheimer DiseaseBrainCognitionCognitive DysfunctionDiffusion Magnetic Resonance ImagingEducational StatusFemaleGenotypeHumansLinear ModelsMaleNerve NetNeuroimagingAPOE4Brain connectivityHARDI tractographyMultivariate analysisNeuroimaging geneticsSeemingly unrelated regression (SUR)

Identifiers

PMID25257986
PMCPMC4276318

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.