Evidence map›Paper›PMID 28098719›Full record

ArticlePsychosomatic medicine2017

Regional Gray Matter Volumes as Related to Psychomotor Slowing in Adults with Type 1 Diabetes.

Karen A Nunley, Christopher M Ryan, Howard J Aizenstein, J Richard Jennings, Rebecca L MacCloud, Trevor J Orchard, Caterina Rosano

Abstract read
In one paragraph

Article in Psychosomatic medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Reproductive health history and later life cognition in African Caribbean women.Alzheimer's & dementia : the journal of the Alzheimer's Association · 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

7 authors at 2 institutions in 1 country.

Karen A NunleyFrom the Department of Epidemiology, University of Pittsburgh Graduate School of Public Health (Nunley, Orchard, Rosano), Pittsburgh, PA; Human Research Protection Program, University of California San Francisco (Ryan), San Francisco, CA; Departments of Psychology and Psychiatry, University of Pittsburgh (Jennings); and Department of Psychiatry, School of Medicine, University of Pittsburgh (Aizenstein, MacCloud), Pittsburgh, PA.
Christopher M Ryan
Howard J Aizenstein
J Richard Jennings
Rebecca L MacCloud
Trevor J Orchard
Caterina Rosano
University of California, San Francisco · USUniversity of Pittsburgh · US

Funding

VARIABILITY, STABILITY & SMOOTHNESS OF WALKINGP30AG024827 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JENNIFER S BRACH · 2004 to 2026
$28.6M
Epidemiology of Diabetes Complications (EDC) Phase II: renewalR37DK034818 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ORCHARD, TREVOR J. · 2009 to 2018
$6.5M
EPIDEMIOLOGY OF DIABETIC COMPLICATIONS--PHASE IIR01DK034818 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COSTACOU, TINA · 1986 to 2019
$5.6M
Imaging biomarkers of accelerated brain aging in Type-1 DiabetesR01DK089028 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ROSANO, CATERINA · 2010 to 2013
$2.3M
The Brain as a Target for Pre and Essential HypertensionR01HL101959 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JENNINGS, JOHN RICHARD · 2010 to 2014
$2.1M
NHLBI NIH HHS R01 HL101959NIA NIH HHS P30 AG024827NIDDK NIH HHS R01 DK034818NIDDK NIH HHS R01 DK089028NIDDK NIH HHS R37 DK034818
6 · The paper itself

Abstract

objectivePsychomotor slowing is a common cognitive complication in type 1 diabetes (T1D), but its neuroanatomical correlates and risk factors are unclear. In nondiabetic adults, smaller gray matter volume (GMV) and presence of white matter hyperintensities are associated with psychomotor slowing. We hypothesize that smaller GMV in prefronto-parietal regions explains T1D-related psychomotor slowing. We also inspect the contribution of microvascular disease and hyperglycemia.

methodsGMV, white matter hyperintensities (WMH), and glucose levels were measured concurrently with a test of psychomotor speed (Digit Symbol Substitution Test [DSST]) in 95 adults with childhood-onset T1D (mean age/duration = 49/41 years) and 135 similarly aged non-T1D adults. Linear regression models tested associations between DSST and regional GMV, controlling for T1D, sex, and education; a bootstrapping method tested whether regional GMV explained between-group differences in DSST. For the T1D cohort, voxel-based and a priori regions-of-interest methods further tested associations between GMV and DSST, adjusting for WMH, hyperglycemia, and age.

resultsBilateral putamen, but no other regions examined, significantly attenuated DSST differences between the cohorts (bootstrapped unstandardized indirect effects: -3.49, -3.26; 95% confidence interval = -5.49 to -1.80, -5.29 to -1.44, left and right putamen, respectively). Among T1D, DSST was positively associated with GMV of bilateral putamen and left thalamus. Neither WMH, hyperglycemia, age, nor other factors substantially modified these relationships.

conclusionsFor middle-aged adults with T1D and cerebral microvascular disease, GMV of basal ganglia may play a critical role in regulating psychomotor speed, as measured via DSST. Studies to quantify the impact of basal ganglia atrophy concurrent with WMH progression on psychomotor slowing are warranted.

Indexed as

Cerebral Small Vessel DiseasesCognitive DysfunctionAdultBasal GangliaCohort StudiesDiabetes Mellitus, Type 1FemaleGray MatterHumansMaleMiddle AgedPsychomotor Performance

Identifiers

PMID28098719
PMCPMC5453835
OpenAlexW2576384101

What OpenQuestion holds

Textmetadata
LicenceTDM
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.