Evidence map›Paper›PMID 32804441›Full record

ArticleHuman brain mapping2020

Whole-brain functional connectivity correlates of obesity phenotypes.

Bo-Yong Park, Kyoungseob Byeon, Mi Ji Lee, Chin-Sang Chung, Se-Hong Kim, Filip Morys, Boris Bernhardt, Alain Dagher, Hyunjin Park

Open access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

21 citing papers in PubMed, 33 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

9 authors at 4 institutions in 2 countries.

Bo-Yong ParkMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.ORCID 0000-0001-7096-337X
Kyoungseob ByeonDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea.
Mi Ji LeeDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Chin-Sang ChungDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Se-Hong KimDepartment of Family Medicine, St. Vincent's Hospital, Catholic University College of Medicine, Suwon, South Korea.
Filip MorysMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.ORCID 0000-0001-8996-2676
Boris BernhardtMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.ORCID 0000-0001-9256-6041
Alain DagherMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
Hyunjin ParkCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.ORCID 0000-0001-5681-8918
Montreal Neurological Institute and Hospital · CAInstitute for Basic Science · KRSamsung Medical Center · KRThe Catholic University of Korea St. Vincent's Hospital · KR

Funding

Fonds de la Recherche du Québec - Santé (FRQ-S) Postdoctoral TrainingInstitute for Basic Science IBS-R015-D1Korean government under the AI Graduate School Support Program 2019-0-00421MIST (Ministry of Science and ICT) of Korea under the ITRC (Information Technology Research Center) IITP-2020-2018-0-01798 National Research Foundation of Korea (NRF-2020M3E5D2A01084892)Montreal Neurological Institute and Hospital (MNI) Molson Neuro-Engineering Fellowship
6 · The paper itself

Abstract

Dysregulated neural mechanisms in reward and somatosensory circuits result in an increased appetitive drive for and reduced inhibitory control of eating, which in turn causes obesity. Despite many studies investigating the brain mechanisms of obesity, the role of macroscale whole-brain functional connectivity remains poorly understood. Here, we identified a neuroimaging-based functional connectivity pattern associated with obesity phenotypes by using functional connectivity analysis combined with machine learning in a large-scale (n ~ 2,400) dataset spanning four independent cohorts. We found that brain regions containing the reward circuit positively associated with obesity phenotypes, while brain regions for sensory processing showed negative associations. Our study introduces a novel perspective for understanding how the whole-brain functional connectivity correlates with obesity phenotypes. Furthermore, we demonstrated the generalizability of our findings by correlating the functional connectivity pattern with obesity phenotypes in three independent datasets containing subjects of multiple ages and ethnicities. Our findings suggest that obesity phenotypes can be understood in terms of macroscale whole-brain functional connectivity and have important implications for the obesity neuroimaging community.

Indexed as

ConnectomeRewardAdultAgedBrainCohort StudiesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNerve NetObesityPhenotypeYoung Adultfunctional connectivitymachine learningobesityUK Biobankwhole-brain connectome

Identifiers

PMID32804441
PMCPMC7643372
OpenAlexW3064032545

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.