Evidence map›Paper›PMID 32723842›Full record

ArticleDiabetes care2020

Erythrocyte n-6 Polyunsaturated Fatty Acids, Gut Microbiota, and Incident Type 2 Diabetes: A Prospective Cohort Study.

Zelei Miao, Jie-Sheng Lin, Yingying Mao, Geng-Dong Chen, Fang-Fang Zeng, Hong-Li Dong, Zengliang Jiang, Jiali Wang, Congmei Xiao, Menglei Shuai and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 8% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 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

15 authors at 4 institutions in 2 countries.

Zelei MiaoZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Jie-Sheng LinGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yingying MaoDepartment of Epidemiology and Biostatistics, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
Geng-Dong ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Fang-Fang ZengGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0001-8650-0927
Hong-Li DongGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Zengliang JiangZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Jiali WangZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Congmei XiaoZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Menglei ShuaiZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Wanglong GouZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Yuanqing FuZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Fumiaki ImamuraMRC Epidemiology Unit, University of Cambridge, Cambridge, U.K.
Yu-Ming ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China zhengjusheng@westlake.edu.cn chenyum@mail.sysu.edu.cn.ORCID 0000-0003-1658-5528
Ju-Sheng ZhengZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China zhengjusheng@westlake.edu.cn chenyum@mail.sysu.edu.cn.ORCID 0000-0001-6560-4890
Westlake University · CNSun Yat-sen University · CNMRC Epidemiology Unit · GBZhejiang Chinese Medical University · CN

Funding

Medical Research Council MC_UU_00006/3Medical Research Council MC_UU_12015/5
6 · The paper itself

Abstract

objectiveTo examine the association of erythrocyte n-6 polyunsaturated fatty acid (PUFA) biomarkers with incident type 2 diabetes and explore the potential role of gut microbiota in the association. RESEARCH DESIGN AND

methodsWe evaluated 2,731 participants without type 2 diabetes recruited between 2008 and 2013 in the Guangzhou Nutrition and Health Study (Guangzhou, China). Case subjects with type 2 diabetes were identified with clinical and biochemical information collected at follow-up visits. Using stool samples collected during the follow-up in the subset (

resultsOver 6.2 years of follow-up, 276 case subjects with type 2 diabetes were identified (risk 0.10). Higher levels of erythrocyte γ-linolenic acid (GLA), but not linoleic or arachidonic acid, were associated with higher type 2 diabetes incidence. Comparing the top to the bottom quartile groups of GLA levels, relative risk was 1.72 (95% CI 1.21, 2.44) adjusted for potential confounders. Baseline GLA was inversely associated with gut microbial richness and diversity (α-diversity, both

conclusionsRelative concentrations of erythrocyte GLA were positively associated with incident type 2 diabetes in a Chinese population and also with gut microbial profiles. These results highlight that gut microbiota may play an important role linking n-6 PUFA metabolism and type 2 diabetes etiology.

Indexed as

AdultAgedArachidonic AcidBiomarkersChinaDiabetes Mellitus, Type 2ErythrocytesFatty Acids, Omega-6Fatty Acids, UnsaturatedFemaleGastrointestinal MicrobiomeHumansIncidenceMaleMiddle AgedProspective StudiesArachidonic AcidBiomarkersFatty Acids, Omega-6Fatty Acids, Unsaturated

Identifiers

PMID32723842
PMCPMC7510039
OpenAlexW3045952487

What OpenQuestion holds

Textmetadata
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.