Evidence map›Paper›PMID 37907866›Full record

SynthesisBMC medicine2023

Early-life exposure to the Great Chinese Famine and gut microbiome disruption across adulthood for type 2 diabetes: three population-based cohort studies.

Wanglong Gou, Huijun Wang, Xin-Yi Tang, Yan He, Chang Su, Jiguo Zhang, Ting-Yu Sun, Zengliang Jiang, Zelei Miao, Yuanqing Fu and 5 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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.

Wanglong Gou *Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Huijun Wang *National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Xin-Yi Tang *The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Yan He *Microbiome Medicine Center, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Chang SuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Jiguo ZhangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Ting-Yu SunGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Zengliang JiangCenter for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Zelei MiaoCenter for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Yuanqing FuCenter for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Hui ZhaoCenter for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Yu-Ming ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China. chenyum@mail.sysu.edu.cn.
Bing ZhangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China. zhangbing@chinacdc.cn.
Hongwei ZhouMicrobiome Medicine Center, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China. hzhou@smu.edu.cn.
Ju-Sheng ZhengCenter for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China. zhengjusheng@westlake.edu.cn.ORCID 0000-0001-6560-4890

Funding

MONITORING SOCIAL CHANGE: HEALTH, REPRODUCTION, AGINGR01HD030880 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 1994 to 2024
$27.0M
Program Development (Pilot) CoreP30AG066615 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELIZABETH A FRANKENBERG · 2020 to 2026
$4.1M
Monitoring Social Change: Dynamics Of Aging And Cognitive FunctionR01AG065357 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 2020 to 2024
$3.6M
Translational Neuropsychopharmacology Research of Nicotine AddictionR01DA038700 · NIDA · UNIVERSITY OF MISSOURI-COLUMBIA · PI FROELIGER, BRETT, GRAY, KEVIN M · 2015 to 2019
$2.9M
NIA NIH HHS P30 AG066615NIA NIH HHS R01 AG065357NICHD NIH HHS R01 HD030880NIDA NIH HHS R01 DA038700
6 · The paper itself

Abstract

backgroundThe early life stage is critical for the gut microbiota establishment and development. We aimed to investigate the lifelong impact of famine exposure during early life on the adult gut microbial ecosystem and examine the association of famine-induced disturbance in gut microbiota with type 2 diabetes.

methodsWe profiled the gut microbial composition among 11,513 adults (18-97 years) from three independent cohorts and examined the association of famine exposure during early life with alterations of adult gut microbial diversity and composition. We performed co-abundance network analyses to identify keystone taxa in the three cohorts and constructed an index with the shared keystone taxa across the three cohorts. Among each cohort, we used linear regression to examine the association of famine exposure during early life with the keystone taxa index and assessed the correlation between the keystone taxa index and type 2 diabetes using logistic regression adjusted for potential confounders. We combined the effect estimates from the three cohorts using random-effects meta-analysis.

resultsCompared with the no-exposed control group (born during 1962-1964), participants who were exposed to the famine during the first 1000 days of life (born in 1959) had consistently lower gut microbial alpha diversity and alterations in the gut microbial community during adulthood across the three cohorts. Compared with the no-exposed control group, participants who were exposed to famine during the first 1000 days of life were associated with consistently lower levels of keystone taxa index in the three cohorts (pooled beta - 0.29, 95% CI - 0.43, - 0.15). Per 1-standard deviation increment in the keystone taxa index was associated with a 13% lower risk of type 2 diabetes (pooled odds ratio 0.87, 95% CI 0.80, 0.93), with consistent results across three individual cohorts.

conclusionsThese findings reveal a potential role of the gut microbiota in the developmental origins of health and disease (DOHaD) hypothesis, deepening our understanding about the etiology of type 2 diabetes.

Indexed as

Diabetes Mellitus, Type 2Gastrointestinal MicrobiomePrenatal Exposure Delayed EffectsStarvationAdolescentAdultAgedAged, 80 and overChinaCohort StudiesEast Asian PeopleFamineHumansMicrobiotaMiddle AgedYoung AdultDOHaDFamineGut microbiomeType 2 diabetes

Identifiers

PMID37907866
PMCPMC10619253

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.