Evidence map›Paper›PMID 25003029›Full record

ArticleNeuroImage. Clinical2014

Changes in MEG resting-state networks are related to cognitive decline in type 1 diabetes mellitus patients.

Matteo Demuru, Eelco van Duinkerken, Matteo Fraschini, Francesco Marrosu, Frank J Snoek, Frederik Barkhof, Martin Klein, Michaela Diamant, Arjan Hillebrand

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Differential Resting State Connectivity Responses to Glycemic State in Type 1 Diabetes.The Journal of clinical endocrinology and metabolism · 2020
    Observational
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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

9 authors.

Matteo DemuruDepartment of Electrical and Electronic Engineering, University of Cagliari, Italy ; Department of Public Health, Clinic and Molecular Medicine, University of Cagliari, Italy.
Eelco van DuinkerkenDepartment of Medical Psychology, VU University Medical Centre, Amsterdam, The Netherlands ; Diabetes Centre/Department of Internal Medicine, VU University Medical Centre, Amsterdam, The Netherlands.
Matteo FraschiniDepartment of Electrical and Electronic Engineering, University of Cagliari, Italy.
Francesco MarrosuDepartment of Public Health, Clinic and Molecular Medicine, University of Cagliari, Italy.
Frank J SnoekDepartment of Medical Psychology, VU University Medical Centre, Amsterdam, The Netherlands.
Frederik BarkhofDepartment of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands.
Martin KleinDepartment of Medical Psychology, VU University Medical Centre, Amsterdam, The Netherlands.
Michaela DiamantDiabetes Centre/Department of Internal Medicine, VU University Medical Centre, Amsterdam, The Netherlands.
Arjan HillebrandDepartment of Clinical Neurophysiology and MEG Centre, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIntegrity of resting-state functional brain networks (RSNs) is important for proper cognitive functioning. In type 1 diabetes mellitus (T1DM) cognitive decrements are commonly observed, possibly due to alterations in RSNs, which may vary according to microvascular complication status. Thus, we tested the hypothesis that functional connectivity in RSNs differs according to clinical status and correlates with cognition in T1DM patients, using an unbiased approach with high spatio-temporal resolution functional network.

methodsResting-state magnetoencephalographic (MEG) data for T1DM patients with (n = 42) and without (n = 41) microvascular complications and 33 healthy participants were recorded. MEG time-series at source level were reconstructed using a recently developed atlas-based beamformer. Functional connectivity within classical frequency bands, estimated by the phase lag index (PLI), was calculated within eight commonly found RSNs. Neuropsychological tests were used to assess cognitive performance, and the relation with RSNs was evaluated.

resultsSignificant differences in terms of RSN functional connectivity between the three groups were observed in the lower alpha band, in the default-mode (DMN), executive control (ECN) and sensorimotor (SMN) RSNs. T1DM patients with microvascular complications showed the weakest functional connectivity in these networks relative to the other groups. For DMN, functional connectivity was higher in patients without microangiopathy relative to controls (all p < 0.05). General cognitive performance for both patient groups was worse compared with healthy controls. Lower DMN alpha band functional connectivity correlated with poorer general cognitive ability in patients with microvascular complications. DISCUSSION: Altered RSN functional connectivity was found in T1DM patients depending on clinical status. Lower DMN functional connectivity was related to poorer cognitive functioning. These results indicate that functional connectivity may play a key role in T1DM-related cognitive dysfunction.

Indexed as

AdultBrainBrain MappingCognitionCognition DisordersDiabetes Mellitus, Type 1FemaleHumansMagnetoencephalographyMaleMiddle AgedNerve NetNeuropsychological TestsFunctional connectivityMagnetoencephalographyOscillationsPhase Lag Index (PLI)Resting-state networksType 1 diabetes mellitus

Identifiers

PMID25003029
PMCPMC4081980

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LicenceCC BY-NC-ND
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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.