Evidence map›Paper›PMID 37261829›Full record

Trial reportJAMA network open2023

Patterns of Regional Brain Atrophy and Brain Aging in Middle- and Older-Aged Adults With Type 1 Diabetes.

Mohamad Habes, Alan M Jacobson, Barbara H Braffett, Tanweer Rashid, Christopher M Ryan, Haochang Shou, Yuhan Cui, Christos Davatzikos, Jose A Luchsinger, Geert J Biessels and 5 more

Open access · goldAbstract readRandomized Controlled TrialObservational Study
In one paragraph

Trial report in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Thalamic Nuclei Atrophy in Type 1 Diabetes Mellitus Across Disease Duration.Journal of magnetic resonance imaging : JMRI · 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

15 authors at 7 institutions in 2 countries.

Mohamad HabesNeuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Alan M JacobsonNYU Long Island School of Medicine, NYU Langone Hospital-Long Island, Mineola, New York.
Barbara H BraffettGeorge Washington University, Biostatistics Center, Rockville, Maryland.
Tanweer RashidNeuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Christopher M RyanUniversity of Pittsburgh, Pittsburgh, Pennsylvania.
Haochang ShouCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Yuhan CuiCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Jose A LuchsingerColumbia University Irving Medical Center, New York, New York.
Geert J BiesselsDepartment of Neurology, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands.
Ionut BebuGeorge Washington University, Biostatistics Center, Rockville, Maryland.
Rose A Gubitosi-KlugCase Western Reserve University School of Medicine, Rainbow Babies and Children's Hospital, Cleveland, Ohio.
R Nick BryanCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Ilya M NasrallahCenter for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
DCCT/EDIC Research Group
University of Pennsylvania · USGeorge Washington University · USCase Western Reserve University · USColumbia University Irving Medical Center · USThe University of Texas Health Science Center at San Antonio · USUniversity Medical Center Utrecht · NLUniversity of Pittsburgh · US

Funding

Limited Competition for the Continuation of Epidemiology of Diabetes Interventions and Complications (EDIC) Study Clinical Research Center (Collaborative U01)U01DK094157 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI Ionut Bebu, Barbara Halina Braffett · 2011 to 2026
$97.6M
Epidemiology of Diabetes Interventions and Complications Data Coordinating CenterU01DK094176 · NIDDK · GEORGE WASHINGTON UNIVERSITY · PI BEBU, IONUT, BRAFFETT, BARBARA HALINA · 2012 to 2022
$30.8M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0M
The Neuroimaging Brain Chart Software SuiteU24NS130411 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos, Yong Fan · 2023 to 2026
$3.7M
Multiethnic machine learning brain signatures of ADRDR01AG080821 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI HABES, MOHAMAD · 2022 to 2025
$2.9M
Midcareer Award for Research in Dementia Risk Factors and PreventionK24AG045334 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Jose Alejandro Luchsinger · 2016 to 2026
$1.5M
NIA NIH HHS K24 AG045334NIA NIH HHS R01 AG080821NIBIB NIH HHS R01 EB022573NIDDK NIH HHS P30 DK111022NIDDK NIH HHS U01 DK094157NIDDK NIH HHS U01 DK094176NINDS NIH HHS U24 NS130411
6 · The paper itself

Abstract

Importance: Little is known about structural brain changes in type 1 diabetes (T1D) and whether there are early manifestations of a neurodegenerative condition like Alzheimer disease (AD) or evidence of premature brain aging. Objective: To evaluate neuroimaging markers of brain age and AD-like atrophy in participants with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, identify which brain regions are associated with the greatest changes in patients with T1D, and assess the association between cognition and brain aging indices. Design, Setting, and Participants: This cohort study leveraged data collected during the combined DCCT (randomized clinical trial, 1983-1993) and EDIC (observational study, 1994 to present) studies at 27 clinical centers in the US and Canada. A total of 416 eligible EDIC participants and 99 demographically similar adults without diabetes were enrolled in the magnetic resonance imaging (MRI) ancillary study, which reports cross-sectional data collected in 2018 to 2019 and relates it to factors measured longitudinally in DCCT/EDIC. Data analyses were performed between July 2020 and April 2022. Exposure: T1D diagnosis. Main Outcomes and Measures: Psychomotor and mental efficiency were evaluated using verbal fluency, digit symbol substitution test, trail making part B, and the grooved pegboard. Immediate memory scores were derived from the logical memory subtest of the Wechsler memory scale and the Wechsler digit symbol substitution test. MRI and machine learning indices were calculated to predict brain age and quantify AD-like atrophy. Results: This study included 416 EDIC participants with a median (range) age of 60 (44-74) years (87 of 416 [21%] were older than 65 years) and a median (range) diabetes duration of 37 (30-51) years. EDIC participants had consistently higher brain age values compared with controls without diabetes, indicative of approximately 6 additional years of brain aging (EDIC participants: β, 6.16; SE, 0.71; control participants: β, 1.04; SE, 0.04; P < .001). In contrast, AD regional atrophy was comparable between the 2 groups. Regions with atrophy in EDIC participants vs controls were observed mainly in the bilateral thalamus and putamen. Greater brain age was associated with lower psychomotor and mental efficiency among EDIC participants (β, -0.04; SE, 0.01; P < .001), but not among controls. Conclusions and Relevance: The findings of this study suggest an increase in brain aging among individuals with T1D without any early signs of AD-related neurodegeneration. These increases were associated with reduced cognitive performance, but overall, the abnormal patterns seen in this sample were modest, even after a mean of 38 years with T1D.

Indexed as

Alzheimer DiseaseDiabetes ComplicationsDiabetes Mellitus, Type 1AdultAgingAtrophyBrainChildCohort StudiesCross-Sectional StudiesHumansMiddle Aged

Identifiers

PMID37261829
PMCPMC10236234
OpenAlexW4378953128

What OpenQuestion holds

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LicenceCC BY
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.