Evidence map›Paper›PMID 31568716›Full record

ArticleBrain and behavior2019

Aberrant patterns of default-mode network functional connectivity associated with metabolic syndrome: A resting-state study.

Barnaly Rashid, Sheena I Dev, Michael Esterman, Nicolette F Schwarz, Tori Ferland, Francesca C Fortenbaugh, William P Milberg, Regina E McGlinchey, David H Salat, Elizabeth C Leritz

Open access · goldAbstract read
In one paragraph

Article in Brain and behavior, 2019. 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
1.9field-weighted citation impact, top 15% 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, 24 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Barnaly RashidNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.ORCID 0000-0002-3602-5109
Sheena I DevHarvard Medical School, Boston, Massachusetts.
Michael EstermanNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.ORCID 0000-0002-9000-3920
Nicolette F SchwarzNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.
Tori FerlandNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.
Francesca C FortenbaughNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.ORCID 0000-0002-8585-1589
William P MilbergNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.
Regina E McGlincheyNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.
David H SalatNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.
Elizabeth C LeritzNeuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.ORCID 0000-0002-6567-6605
Harvard University · USBoston University · US

Funding

Neuroimaging and Neuropsychological Biomarkers of Vascular Risk FactorsR01NS086882 · NINDS · HARVARD MEDICAL SCHOOL · PI LERITZ, ELIZABETH C · 2014 to 2018
$1.7M
6 · The paper itself

Abstract

introductionMetabolic syndrome (MetS) is a clustering of three or more cardiovascular risk factors (RF), including hypertension, obesity, high cholesterol, or hyperglycemia. MetS and its component RFs are more prevalent in older age, and can be accompanied by alterations in brain structure. Studies have shown altered functional connectivity (FC) in samples with individual RFs as well as in clinical populations that are at higher risk to develop MetS. These studies have indicated that the default mode network (DMN) may be particularly vulnerable, yet little is known about the overall impact of MetS on FC in this network.

methodsIn this study, we evaluated the integrity of FC to the DMN in participants with MetS relative to non-MetS individuals. Using a seed-based connectivity analysis approach, resting-state functional MRI (fMRI) data were analyzed, and the FC measures among the DMN seed (isthmus of the cingulate) and rest of the brain voxels were estimated.

resultsParticipants with MetS demonstrated reduced positive connectivity between the DMN seed and left superior frontal regions, and reduced negative connectivity between the DMN seed and left superior parietal, left postcentral, right precentral, right superior temporal and right superior parietal regions, after accounting for age- and sex-effects.

conclusionsOur results suggest that MetS is associated with alterations in FC between the DMN and other regions of the brain. Furthermore, these results indicate that the overall burden of vascular RFs associated with MetS may, in part, contribute to the pathophysiology underlying aberrant FC in the DMN.

Indexed as

AgedBrain DiseasesBrain MappingFemaleFrontal LobeHumansMagnetic Resonance ImagingMaleMetabolic SyndromeMiddle AgedNeural PathwaysParietal Lobedefault mode networkfunctional connectivitymetabolic syndromeresting-state fMRIseed-based analysis

Identifiers

PMID31568716
PMCPMC6908882
OpenAlexW2977901079

What OpenQuestion holds

Textmetadata
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.