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Published in: BMC Medicine 1/2022

01-12-2022 | Obesity | Research article

Temporal relationship among adiposity, gut microbiota, and insulin resistance in a longitudinal human cohort

Authors: Kui Deng, Menglei Shuai, Zheqing Zhang, Zengliang Jiang, Yuanqing Fu, Luqi Shen, Ju-Sheng Zheng, Yu-ming Chen

Published in: BMC Medicine | Issue 1/2022

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Abstract

Background

The temporal relationship between adiposity and gut microbiota was unexplored. Whether some gut microbes lie in the pathways from adiposity to insulin resistance is less clear. Our study aims to reveal the temporal relationship between adiposity and gut microbiota and investigate whether gut microbiota may mediate the association of adiposity with insulin resistance in a longitudinal human cohort study.

Methods

We obtained repeated-measured gut shotgun metagenomic and anthropometric data from 426 Chinese participants over ~3 years of follow-up. Cross-lagged path analysis was used to examine the temporal relationship between BMI and gut microbial features. The associations between the gut microbes and insulin resistance-related phenotypes were examined using a linear mixed-effect model. We examined the mediation effect of gut microbes on the association between adiposity and insulin resistance-related phenotypes. Replication was performed in the HMP cohort.

Results

Baseline BMI was prospectively associated with levels of ten gut microbial species. Among them, results of four species (Adlercreutzia equolifaciens, Parabacteroides unclassified, Lachnospiraceae bacterium 3 1 57FAA CT1, Lachnospiraceae bacterium 7 1 58FAA) were replicated in the independent HMP cohort. Lachnospiraceae bacterium 3 1 57FAA CT1 was inversely associated with HOMA-IR and fasting insulin. Lachnospiraceae bacterium 3 1 57FAA CT1 mediated the association of overweight/obesity with HOMA-IR (FDR<0.05). Furthermore, Lachnospiraceae bacterium 3 1 57FAA CT1 was positively associated with the butyrate-producing pathway PWY-5022 (p < 0.001).

Conclusions

Our study identified one potentially beneficial microbe Lachnospiraceae bacterium 3 1 57FAA CT1, which might mediate the effect of adiposity on insulin resistance. The identified microbes are helpful for the discovery of novel therapeutic targets, as to mitigate the impact of adiposity on insulin resistance.
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Literature
3.
go back to reference Liu R, Hong J, Xu X, Feng Q, Zhang D, Gu Y, et al. Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat Med. 2017;23(7):859–68.PubMedCrossRef Liu R, Hong J, Xu X, Feng Q, Zhang D, Gu Y, et al. Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat Med. 2017;23(7):859–68.PubMedCrossRef
4.
go back to reference Ridaura VK, Faith JJ, Rey FE, Cheng J, Duncan AE, Kau AL, et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science. 2013;341(6150):1241214.PubMedCrossRef Ridaura VK, Faith JJ, Rey FE, Cheng J, Duncan AE, Kau AL, et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science. 2013;341(6150):1241214.PubMedCrossRef
5.
go back to reference Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol. 2021;19(1):55–71.PubMedCrossRef Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol. 2021;19(1):55–71.PubMedCrossRef
6.
go back to reference Lv Y, Qin X, Jia H, Chen S, Sun W, Wang X. The association between gut microbiota composition and BMI in Chinese male college students, as analysed by next-generation sequencing. Br J Nutr. 2019;122(9):986–95.PubMedCrossRef Lv Y, Qin X, Jia H, Chen S, Sun W, Wang X. The association between gut microbiota composition and BMI in Chinese male college students, as analysed by next-generation sequencing. Br J Nutr. 2019;122(9):986–95.PubMedCrossRef
7.
go back to reference Palmas V, Pisanu S, Madau V, Casula E, Deledda A, Cusano R, et al. Gut microbiota markers associated with obesity and overweight in Italian adults. Sci Rep. 2021;11(1):5532.PubMedPubMedCentralCrossRef Palmas V, Pisanu S, Madau V, Casula E, Deledda A, Cusano R, et al. Gut microbiota markers associated with obesity and overweight in Italian adults. Sci Rep. 2021;11(1):5532.PubMedPubMedCentralCrossRef
8.
go back to reference Cani PD, Van Hul M. Gut microbiota and obesity: causally linked? Expert Rev Gastroenterol Hepatol. 2020;14(6):401–3.PubMedCrossRef Cani PD, Van Hul M. Gut microbiota and obesity: causally linked? Expert Rev Gastroenterol Hepatol. 2020;14(6):401–3.PubMedCrossRef
9.
go back to reference Chen L, Wang D, Garmaeva S, Kurilshikov A, Vich Vila A, Gacesa R, et al. The long-term genetic stability and individual specificity of the human gut microbiome. Cell. 2021;184(9):2302–2315.e2312.PubMedCrossRef Chen L, Wang D, Garmaeva S, Kurilshikov A, Vich Vila A, Gacesa R, et al. The long-term genetic stability and individual specificity of the human gut microbiome. Cell. 2021;184(9):2302–2315.e2312.PubMedCrossRef
10.
go back to reference Frost F, Kacprowski T, Rühlemann M, Pietzner M, Bang C, Franke A, et al. Long-term instability of the intestinal microbiome is associated with metabolic liver disease, low microbiota diversity, diabetes mellitus and impaired exocrine pancreatic function. Gut. 2021;70(3):522–30.PubMedCrossRef Frost F, Kacprowski T, Rühlemann M, Pietzner M, Bang C, Franke A, et al. Long-term instability of the intestinal microbiome is associated with metabolic liver disease, low microbiota diversity, diabetes mellitus and impaired exocrine pancreatic function. Gut. 2021;70(3):522–30.PubMedCrossRef
11.
go back to reference Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, et al. Genomic variation landscape of the human gut microbiome. Nature. 2013;493(7430):45–50.PubMedCrossRef Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, et al. Genomic variation landscape of the human gut microbiome. Nature. 2013;493(7430):45–50.PubMedCrossRef
12.
go back to reference David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505(7484):559–63.PubMedCrossRef David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505(7484):559–63.PubMedCrossRef
13.
go back to reference Mueller S, Saunier K, Hanisch C, Norin E, Alm L, Midtvedt T, et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study. Appl Environ Microbiol. 2006;72(2):1027–33.PubMedPubMedCentralCrossRef Mueller S, Saunier K, Hanisch C, Norin E, Alm L, Midtvedt T, et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study. Appl Environ Microbiol. 2006;72(2):1027–33.PubMedPubMedCentralCrossRef
14.
go back to reference Liu B, Woo J, Tang N, Ng K, Ip R, Yu A. Assessment of total energy expenditure in a Chinese population by a physical activity questionnaire: examination of validity. Int J Food Sci Nutr. 2001;52(3):269–82.PubMedCrossRef Liu B, Woo J, Tang N, Ng K, Ip R, Yu A. Assessment of total energy expenditure in a Chinese population by a physical activity questionnaire: examination of validity. Int J Food Sci Nutr. 2001;52(3):269–82.PubMedCrossRef
15.
go back to reference Zhang CX, Ho SC. Validity and reproducibility of a food frequency Questionnaire among Chinese women in Guangdong province. Asia Pac J Clin Nutr. 2009;18(2):240–50.PubMed Zhang CX, Ho SC. Validity and reproducibility of a food frequency Questionnaire among Chinese women in Guangdong province. Asia Pac J Clin Nutr. 2009;18(2):240–50.PubMed
16.
go back to reference Hanley AJ, Williams K, Stern MP, Haffner SM. Homeostasis model assessment of insulin resistance in relation to the incidence of cardiovascular disease: the San Antonio Heart Study. Diabetes Care. 2002;25(7):1177–84.PubMedCrossRef Hanley AJ, Williams K, Stern MP, Haffner SM. Homeostasis model assessment of insulin resistance in relation to the incidence of cardiovascular disease: the San Antonio Heart Study. Diabetes Care. 2002;25(7):1177–84.PubMedCrossRef
17.
go back to reference Shuai M, Zhang G, Zeng FF, Fu Y, Liang X, Yuan L, et al. Human gut antibiotic resistome and progression of diabetes. Adv Sci (Weinh). 2022;9(11):e2104965. Shuai M, Zhang G, Zeng FF, Fu Y, Liang X, Yuan L, et al. Human gut antibiotic resistome and progression of diabetes. Adv Sci (Weinh). 2022;9(11):e2104965.
19.
go back to reference Truong DT, Franzosa EA, Tickle TL, Scholz M, Weingart G, Pasolli E, et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat Methods. 2015;12(10):902–3.PubMedCrossRef Truong DT, Franzosa EA, Tickle TL, Scholz M, Weingart G, Pasolli E, et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat Methods. 2015;12(10):902–3.PubMedCrossRef
20.
go back to reference Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol. 2012;8(6):e1002358.PubMedPubMedCentralCrossRef Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol. 2012;8(6):e1002358.PubMedPubMedCentralCrossRef
21.
go back to reference Caspi R, Billington R, Ferrer L, Foerster H, Fulcher CA, Keseler IM, et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 2016;44(D1):D471–80.PubMedCrossRef Caspi R, Billington R, Ferrer L, Foerster H, Fulcher CA, Keseler IM, et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 2016;44(D1):D471–80.PubMedCrossRef
22.
go back to reference Caspi R, Billington R, Fulcher CA, Keseler IM, Kothari A, Krummenacker M, et al. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 2017;46(D1):D633–9.PubMedCentralCrossRef Caspi R, Billington R, Fulcher CA, Keseler IM, Kothari A, Krummenacker M, et al. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 2017;46(D1):D633–9.PubMedCentralCrossRef
23.
go back to reference Kenny DA. Cross-lagged panel correlation: a test for spuriousness. Psychol Bull. 1975;82(6):887.CrossRef Kenny DA. Cross-lagged panel correlation: a test for spuriousness. Psychol Bull. 1975;82(6):887.CrossRef
24.
go back to reference Sun D, Zhang T, Su S, Hao G, Chen T, Li Q-Z, et al. Body mass index drives changes in DNA methylation: a longitudinal study. Circ Res. 2019;125(9):824–33.PubMedPubMedCentralCrossRef Sun D, Zhang T, Su S, Hao G, Chen T, Li Q-Z, et al. Body mass index drives changes in DNA methylation: a longitudinal study. Circ Res. 2019;125(9):824–33.PubMedPubMedCentralCrossRef
25.
go back to reference Wu S, Jin C, Li S, Zheng X, Zhang X, Cui L, et al. Aging, arterial stiffness, and blood pressure association in Chinese adults. Hypertension. 2019;73(4):893–9.PubMedCrossRef Wu S, Jin C, Li S, Zheng X, Zhang X, Cui L, et al. Aging, arterial stiffness, and blood pressure association in Chinese adults. Hypertension. 2019;73(4):893–9.PubMedCrossRef
26.
go back to reference Rosseel Y. Lavaan: an R package for structural equation modeling and more. Version 0.5–12 (BETA). J Stat Softw. 2012;48(2):1–36.CrossRef Rosseel Y. Lavaan: an R package for structural equation modeling and more. Version 0.5–12 (BETA). J Stat Softw. 2012;48(2):1–36.CrossRef
27.
go back to reference Jöreskog K. Modeling development: using covariance structure models in longitudinal research. Eur Child Adolescent Psychiatry. 1996;5(1):8–10.CrossRef Jöreskog K. Modeling development: using covariance structure models in longitudinal research. Eur Child Adolescent Psychiatry. 1996;5(1):8–10.CrossRef
28.
go back to reference Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14(6):927–30.CrossRef Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14(6):927–30.CrossRef
29.
go back to reference Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10(1):101–29.CrossRef Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10(1):101–29.CrossRef
30.
go back to reference Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong DT, et al. Accessible, curated metagenomic data through ExperimentHub. Nat Methods. 2017;14(11):1023–4.PubMedPubMedCentralCrossRef Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong DT, et al. Accessible, curated metagenomic data through ExperimentHub. Nat Methods. 2017;14(11):1023–4.PubMedPubMedCentralCrossRef
32.
33.
go back to reference Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.CrossRef Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.CrossRef
34.
go back to reference Zhou B. Prospective study for cut-off points of body mass index in Chinese adults. Zhonghua Liu Xing Bing Xue Za Zhi. 2002;23(6):431–4.PubMed Zhou B. Prospective study for cut-off points of body mass index in Chinese adults. Zhonghua Liu Xing Bing Xue Za Zhi. 2002;23(6):431–4.PubMed
35.
go back to reference Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:1406.5823;2014. Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:1406.5823;2014.
36.
go back to reference Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. Mediation: R package for causal mediation analysis; 2014. Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. Mediation: R package for causal mediation analysis; 2014.
37.
go back to reference Vacca M, Celano G, Calabrese FM, Portincasa P, Gobbetti M, De Angelis M. The controversial role of human gut Lachnospiraceae. Microorganisms. 2020;8(4):573. Vacca M, Celano G, Calabrese FM, Portincasa P, Gobbetti M, De Angelis M. The controversial role of human gut Lachnospiraceae. Microorganisms. 2020;8(4):573.
38.
go back to reference Larrick JW, Mendelsohn AR, Larrick JW. Beneficial gut microbiome remodeled during intermittent fasting in humans. Rejuvenation Res. 2021;24(3):234–7.PubMedCrossRef Larrick JW, Mendelsohn AR, Larrick JW. Beneficial gut microbiome remodeled during intermittent fasting in humans. Rejuvenation Res. 2021;24(3):234–7.PubMedCrossRef
39.
go back to reference Anand S, Kaur H, Mande SS. Comparative in silico analysis of butyrate production pathways in gut commensals and pathogens. Front Microbiol. 1945;2016:7. Anand S, Kaur H, Mande SS. Comparative in silico analysis of butyrate production pathways in gut commensals and pathogens. Front Microbiol. 1945;2016:7.
40.
go back to reference Bianchi F, Duque A, Saad SMI, Sivieri K. Gut microbiome approaches to treat obesity in humans. Appl Microbiol Biotechnol. 2019;103(3):1081–94.PubMedCrossRef Bianchi F, Duque A, Saad SMI, Sivieri K. Gut microbiome approaches to treat obesity in humans. Appl Microbiol Biotechnol. 2019;103(3):1081–94.PubMedCrossRef
41.
go back to reference Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102(31):11070–5.PubMedPubMedCentralCrossRef Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102(31):11070–5.PubMedPubMedCentralCrossRef
42.
go back to reference Chen C, Ye Y, Zhang Y, Pan XF, Pan A. Weight change across adulthood in relation to all cause and cause specific mortality: prospective cohort study. BMJ. 2019;367:l5584.PubMedPubMedCentralCrossRef Chen C, Ye Y, Zhang Y, Pan XF, Pan A. Weight change across adulthood in relation to all cause and cause specific mortality: prospective cohort study. BMJ. 2019;367:l5584.PubMedPubMedCentralCrossRef
43.
go back to reference Liu G, Hu Y, Zong G, Pan A, Manson JE, Rexrode KM, et al. Smoking cessation and weight change in relation to cardiovascular disease incidence and mortality in people with type 2 diabetes: a population-based cohort study. Lancet Diabetes Endocrinol. 2020;8(2):125–33.PubMedPubMedCentralCrossRef Liu G, Hu Y, Zong G, Pan A, Manson JE, Rexrode KM, et al. Smoking cessation and weight change in relation to cardiovascular disease incidence and mortality in people with type 2 diabetes: a population-based cohort study. Lancet Diabetes Endocrinol. 2020;8(2):125–33.PubMedPubMedCentralCrossRef
44.
go back to reference Ling Z, Jin C, Xie T, Cheng Y, Li L, Wu N. Alterations in the fecal microbiota of patients with HIV-1 infection: an observational study in a Chinese population. Sci Rep. 2016;6:30673.PubMedPubMedCentralCrossRef Ling Z, Jin C, Xie T, Cheng Y, Li L, Wu N. Alterations in the fecal microbiota of patients with HIV-1 infection: an observational study in a Chinese population. Sci Rep. 2016;6:30673.PubMedPubMedCentralCrossRef
45.
go back to reference Tsalamandris S, Antonopoulos AS, Oikonomou E, Papamikroulis GA, Vogiatzi G, Papaioannou S, et al. The role of inflammation in diabetes: current concepts and future perspectives. Eur Cardiol. 2019;14(1):50–9.PubMedPubMedCentralCrossRef Tsalamandris S, Antonopoulos AS, Oikonomou E, Papamikroulis GA, Vogiatzi G, Papaioannou S, et al. The role of inflammation in diabetes: current concepts and future perspectives. Eur Cardiol. 2019;14(1):50–9.PubMedPubMedCentralCrossRef
46.
go back to reference Pisanu S, Palmas V, Madau V, Casula E, Deledda A, Cusano R, et al. Impact of a moderately hypocaloric Mediterranean diet on the gut microbiota composition of Italian obese patients. Nutrients. 2020;12(9):2707. Pisanu S, Palmas V, Madau V, Casula E, Deledda A, Cusano R, et al. Impact of a moderately hypocaloric Mediterranean diet on the gut microbiota composition of Italian obese patients. Nutrients. 2020;12(9):2707.
47.
go back to reference Sanna S, van Zuydam NR, Mahajan A, Kurilshikov A, Vich Vila A, Võsa U, et al. Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat Genet. 2019;51(4):600–5.PubMedPubMedCentralCrossRef Sanna S, van Zuydam NR, Mahajan A, Kurilshikov A, Vich Vila A, Võsa U, et al. Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat Genet. 2019;51(4):600–5.PubMedPubMedCentralCrossRef
48.
go back to reference Gao Z, Yin J, Zhang J, Ward RE, Martin RJ, Lefevre M, et al. Butyrate improves insulin sensitivity and increases energy expenditure in mice. Diabetes. 2009;58(7):1509–17.PubMedPubMedCentralCrossRef Gao Z, Yin J, Zhang J, Ward RE, Martin RJ, Lefevre M, et al. Butyrate improves insulin sensitivity and increases energy expenditure in mice. Diabetes. 2009;58(7):1509–17.PubMedPubMedCentralCrossRef
49.
go back to reference Jiang Z, Sun TY, He Y, Gou W, Zuo LS, Fu Y, et al. Dietary fruit and vegetable intake, gut microbiota, and type 2 diabetes: results from two large human cohort studies. BMC Med. 2020;18(1):371.PubMedPubMedCentralCrossRef Jiang Z, Sun TY, He Y, Gou W, Zuo LS, Fu Y, et al. Dietary fruit and vegetable intake, gut microbiota, and type 2 diabetes: results from two large human cohort studies. BMC Med. 2020;18(1):371.PubMedPubMedCentralCrossRef
Metadata
Title
Temporal relationship among adiposity, gut microbiota, and insulin resistance in a longitudinal human cohort
Authors
Kui Deng
Menglei Shuai
Zheqing Zhang
Zengliang Jiang
Yuanqing Fu
Luqi Shen
Ju-Sheng Zheng
Yu-ming Chen
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2022
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-022-02376-3

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