Evidence map›Paper›PMID 37371369›Full record

ArticleBrain sciences2023

Genetic Insights into Obesity and Brain: Combine Mendelian Randomization Study and Gene Expression Analysis.

Leian Chen, Shaokun Zhao, Yuye Wang, Xiaoqian Niu, Bin Zhang, Xin Li, Dantao Peng

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 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

7 authors at 3 institutions in 1 country.

Leian ChenDepartment of Neurology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China.
Shaokun ZhaoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
Yuye WangDepartment of Neurology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China.
Xiaoqian NiuDepartment of Neurology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 100029, China.
Bin ZhangDepartment of Neurology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China.
Xin LiState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-9598-0299
Dantao PengDepartment of Neurology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100029, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing Normal University · CNPeking University · CN

Funding

Central Health Research Project 2020ZD10National Key R&D Program of China 2022YFC2010103National Natural Science Foundation of China 32171085National Natural Science Foundation of China 82071205
6 · The paper itself

Abstract

As a major public-health concern, obesity is imposing an increasing social burden around the world. The link between obesity and brain-health problems has been reported, but controversy remains. To investigate the relationship among obesity, brain-structure changes and diseases, a two-stage analysis was performed. At first, we used the Mendelian-randomization (MR) approach to identify the causal relationship between obesity and cerebral structure. Obesity-related data were retrieved from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and the UK Biobank, whereas the cortical morphological data were from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Further, we extracted region-specific expressed genes according to the Allen Human Brian Atlas (AHBA) and carried out a series of bioinformatics analyses to find the potential mechanism of obesity and diseases. In the univariable MR, a higher body mass index (BMI) or larger visceral adipose tissue (VAT) was associated with a smaller global cortical thickness (

Indexed as

body mass indexcerebral cortexcognitive impairmentgene expressionMendelian randomization analysisobesity

Identifiers

PMID37371369
PMCPMC10295948
OpenAlexW4379056139

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.