Markers of metabolic health and gut microbiome diversity: findings from two population-based cohort studies.
Adult
Biomarkers
Blood Glucose
/ metabolism
C-Reactive Protein
/ metabolism
Cohort Studies
Energy Metabolism
/ genetics
Feces
/ microbiology
Female
Finland
Gastrointestinal Microbiome
/ genetics
Glycated Hemoglobin
/ metabolism
Humans
Insulin Resistance
/ genetics
Male
Metabolic Syndrome
/ genetics
Microbiota
/ genetics
Middle Aged
RNA, Ribosomal, 16S
/ genetics
Surveys and Questionnaires
Twin Studies as Topic
United Kingdom
Faecal microbiome
HOMA-IR
Insulin resistance
Metabolic health
Journal
Diabetologia
ISSN: 1432-0428
Titre abrégé: Diabetologia
Pays: Germany
ID NLM: 0006777
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
received:
28
09
2020
accepted:
08
03
2021
pubmed:
11
6
2021
medline:
19
3
2022
entrez:
10
6
2021
Statut:
ppublish
Résumé
The gut microbiome is hypothesised to be related to insulin resistance and other metabolic variables. However, data from population-based studies are limited. We investigated associations between serologic measures of metabolic health and the gut microbiome in the Northern Finland Birth Cohort 1966 (NFBC1966) and the TwinsUK cohort. Among 506 individuals from the NFBC1966 with available faecal microbiome (16S rRNA gene sequence) data, we estimated associations between gut microbiome diversity metrics and serologic levels of HOMA for insulin resistance (HOMA-IR), HbA In NFBC1966, alpha diversity was lower in individuals with higher HOMA-IR with a mean of 74.4 (95% CI 70.7, 78.3) amplicon sequence variants (ASVs) for the first quartile of HOMA-IR and 66.6 (95% CI 62.9, 70.4) for the fourth quartile of HOMA-IR. Alpha diversity was also lower with higher HbA Overall, higher levels of HOMA-IR, CRP and HbA
Identifiants
pubmed: 34110438
doi: 10.1007/s00125-021-05464-w
pii: 10.1007/s00125-021-05464-w
pmc: PMC8245388
doi:
Substances chimiques
Biomarkers
0
Blood Glucose
0
Glycated Hemoglobin A
0
RNA, Ribosomal, 16S
0
hemoglobin A1c protein, human
0
C-Reactive Protein
9007-41-4
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1749-1759Subventions
Organisme : Medical Research Council
ID : MR/V005030/1
Pays : United Kingdom
Références
Jaacks LM, Vandevijvere S, Pan A et al (2019) The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol 7(3):231–240. https://doi.org/10.1016/S2213-8587(19)30026-9
doi: 10.1016/S2213-8587(19)30026-9
pubmed: 30704950
pmcid: 7360432
Zheng Y, Ley SH, Hu FB (2018) Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol 14(2):88–98. https://doi.org/10.1038/nrendo.2017.151
doi: 10.1038/nrendo.2017.151
pubmed: 29219149
Taylor R (2012) Insulin Resistance and Type 2 Diabetes. Diabetes 61(4):778–779. https://doi.org/10.2337/db12-0073
doi: 10.2337/db12-0073
pubmed: 22442298
pmcid: 3314346
Kahn SE, Hull RL, Utzschneider KM (2006) Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444(7121):840–846. https://doi.org/10.1038/nature05482
doi: 10.1038/nature05482
pubmed: 17167471
Owei I, Umekwe N, Provo C, Wan J, Dagogo-Jack S (2017) Insulin-sensitive and insulin-resistant obese and non-obese phenotypes: role in prediction of incident pre-diabetes in a longitudinal biracial cohort. BMJ Open Diabetes Res Care 5(1):e000415. https://doi.org/10.1136/bmjdrc-2017-000415
doi: 10.1136/bmjdrc-2017-000415
pubmed: 28878939
pmcid: 5574414
Le Chatelier E, Nielsen T, Qin J et al (2013) Richness of human gut microbiome correlates with metabolic markers. Nature 500(7464):541–546. https://doi.org/10.1038/nature12506
doi: 10.1038/nature12506
pubmed: 23985870
Larsen N, Vogensen FK, van den Berg FWJ et al (2010) Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One 5(2):e9085. https://doi.org/10.1371/journal.pone.0009085
doi: 10.1371/journal.pone.0009085
pubmed: 20140211
pmcid: 2816710
Qin J, Li Y, Cai Z et al (2012) A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490(7418):55–60. https://doi.org/10.1038/nature11450
doi: 10.1038/nature11450
pubmed: 23023125
Lee CJ, Sears CL, Maruthur N (2020) Gut microbiome and its role in obesity and insulin resistance. Ann N Y Acad Sci 1461(1):37–52. https://doi.org/10.1111/nyas.14107
doi: 10.1111/nyas.14107
pubmed: 31087391
Lee CC, Watkins SM, Lorenzo C et al (2016) Branched-Chain Amino Acids and Insulin Metabolism: The Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Care 39(4):582–588. https://doi.org/10.2337/dc15-2284
doi: 10.2337/dc15-2284
pubmed: 26895884
pmcid: 4806771
Pedersen HK, Gudmundsdottir V, Nielsen HB et al (2016) Human gut microbes impact host serum metabolome and insulin sensitivity. Nature 535(7612):376–381. https://doi.org/10.1038/nature18646
doi: 10.1038/nature18646
pubmed: 27409811
Rantakallio P (1988) The longitudinal study of the northern Finland birth cohort of 1966. Paediatr Perinat Epidemiol 2(1):59–88. https://doi.org/10.1111/j.1365-3016.1988.tb00180.x
doi: 10.1111/j.1365-3016.1988.tb00180.x
pubmed: 2976931
Loftfield E, Herzig K-H, Caporaso JG et al (2020) Association of body mass index with fecal microbial diversity and metabolites in the northern Finland birth cohort. Cancer Epidemiol Biomarkers Prev 29(11):2289–2299
Perkiömäki N, Auvinen J, Tulppo MP et al (2016) Association between Birth Characteristics and Cardiovascular Autonomic Function at Mid-Life. PLoS One 11(8):e0161604. https://doi.org/10.1371/journal.pone.0161604
doi: 10.1371/journal.pone.0161604
pubmed: 27552091
pmcid: 4994955
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28(7):412–419. https://doi.org/10.1007/bf00280883
doi: 10.1007/bf00280883
pubmed: 3899825
Vogtmann E, Chen J, Amir A et al (2017) Comparison of Collection Methods for Fecal Samples in Microbiome Studies. Am J Epidemiol 185(2):115–123. https://doi.org/10.1093/aje/kww177
doi: 10.1093/aje/kww177
pubmed: 27986704
pmcid: 5253972
Caporaso JG, Lauber CL, Walters WA et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6(8):1621–1624. https://doi.org/10.1038/ismej.2012.8
doi: 10.1038/ismej.2012.8
pubmed: 22402401
pmcid: 3400413
Sinha R, Abu-Ali G, Vogtmann E et al (2017) Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium. Nat Biotechnol 35(11):1077–1086. https://doi.org/10.1038/nbt.3981
doi: 10.1038/nbt.3981
pubmed: 28967885
pmcid: 5839636
Bolyen E, Rideout JR, Dillon MR et al (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37(8):852–857. https://doi.org/10.1038/s41587-019-0209-9
doi: 10.1038/s41587-019-0209-9
pubmed: 7015180
pmcid: 7015180
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13(7):581–583. https://doi.org/10.1038/nmeth.3869
doi: 10.1038/nmeth.3869
pubmed: 4927377
pmcid: 4927377
Bokulich NA, Kaehler BD, Rideout JR et al (2018) Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6(1):90. https://doi.org/10.1186/s40168-018-0470-z
doi: 10.1186/s40168-018-0470-z
pubmed: 5956843
pmcid: 5956843
DeSantis TZ, Hugenholtz P, Larsen N et al (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72(7):5069–5072. https://doi.org/10.1128/AEM.03006-05
doi: 10.1128/AEM.03006-05
pubmed: 1489311
pmcid: 1489311
Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772–780. https://doi.org/10.1093/molbev/mst010
doi: 10.1093/molbev/mst010
pubmed: 3603318
pmcid: 3603318
Price MN, Dehal PS, Arkin AP (2010) FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS One 5(3):e9490. https://doi.org/10.1371/journal.pone.0009490
doi: 10.1371/journal.pone.0009490
pubmed: 20224823
pmcid: 2835736
Oksanen J, Blanchet FG, Friendly M et al (2019) vegan: Community Ecology Package
Verdi S, Abbasian G, Bowyer RCE et al (2019) TwinsUK: The UK Adult Twin Registry Update. Twin Res Hum Genet 22(6):523–529. https://doi.org/10.1017/thg.2019.65
doi: 10.1017/thg.2019.65
pubmed: 31526404
Jamshidi Y, Snieder H, Wang X, Spector TD, Carter ND, O’Dell SD (2006) Common polymorphisms in SOCS3 are not associated with body weight, insulin sensitivity or lipid profile in normal female twins. Diabetologia 49(2):306–310. https://doi.org/10.1007/s00125-005-0093-3
doi: 10.1007/s00125-005-0093-3
pubmed: 16402267
pmcid: 1364534
Goodrich JK, Davenport ER, Beaumont M et al (2016) Genetic Determinants of the Gut Microbiome in UK Twins. Cell Host Microbe 19(5):731–743. https://doi.org/10.1016/j.chom.2016.04.017
doi: 10.1016/j.chom.2016.04.017
pubmed: 27173935
pmcid: 4915943
Zhao N, Chen J, Carroll IM et al (2015) Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association Test. Am J Hum Genet 96(5):797–807. https://doi.org/10.1016/j.ajhg.2015.04.003
doi: 10.1016/j.ajhg.2015.04.003
pubmed: 25957468
pmcid: 4570290
Rigby RA, Stasinopoulos DM (2005) Generalized additive models for location, scale and shape. J R Stat Soc: Ser C: Appl Stat 54(3):507–554. https://doi.org/10.1111/j.1467-9876.2005.00510.x
doi: 10.1111/j.1467-9876.2005.00510.x
Lozupone CA, Hamady M, Kelley ST, Knight R (2007) Quantitative and Qualitative β Diversity Measures Lead to Different Insights into Factors That Structure Microbial Communities. Appl Environ Microbiol 73(5):1576–1585. https://doi.org/10.1128/AEM.01996-06
doi: 10.1128/AEM.01996-06
pubmed: 17220268
pmcid: 1828774
Vrieze A, Van Nood E, Holleman F et al (2012) Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology 143(4):913–916.e7. https://doi.org/10.1053/j.gastro.2012.06.031
doi: 10.1053/j.gastro.2012.06.031
pubmed: 22728514
pmcid: 22728514
Li G, Xie C, Lu S et al (2017) Intermittent Fasting Promotes White Adipose Browning and Decreases Obesity by Shaping the Gut Microbiota. Cell Metab 26(4):672–685.e4. https://doi.org/10.1016/j.cmet.2017.08.019
doi: 10.1016/j.cmet.2017.08.019
pubmed: 28918936
pmcid: 5668683
Wang L, Li P, Tang Z, Yan X, Feng B (2016) Structural modulation of the gut microbiota and the relationship with body weight: compared evaluation of liraglutide and saxagliptin treatment. Sci Rep 6(1):1–10. https://doi.org/10.1038/srep33251
doi: 10.1038/srep33251
Tremaroli V, Bäckhed F (2012) Functional interactions between the gut microbiota and host metabolism. Nature 489(7415):242–249. https://doi.org/10.1038/nature11552
doi: 10.1038/nature11552
pubmed: 22972297
Saad MJA, Santos A, Prada PO (2016) Linking Gut Microbiota and Inflammation to Obesity and Insulin Resistance. Physiology 31(4):283–293. https://doi.org/10.1152/physiol.00041.2015
doi: 10.1152/physiol.00041.2015
pubmed: 27252163
Rivière A, Selak M, Lantin D, Leroy F, De Vuyst L (2016) Bifidobacteria and Butyrate-Producing Colon Bacteria: Importance and Strategies for Their Stimulation in the Human Gut. Front Microbiol 7:979. https://doi.org/10.3389/fmicb.2016.00979
doi: 10.3389/fmicb.2016.00979
pubmed: 27446020
pmcid: 4923077
Tolhurst G, Heffron H, Lam YS et al (2012) Short-Chain Fatty Acids Stimulate Glucagon-Like Peptide-1 Secretion via the G-Protein–Coupled Receptor FFAR2. Diabetes 61(2):364–371. https://doi.org/10.2337/db11-1019
doi: 10.2337/db11-1019
pubmed: 22190648
pmcid: 3266401
Kimura I, Ozawa K, Inoue D et al (2013) The gut microbiota suppresses insulin-mediated fat accumulation via the short-chain fatty acid receptor GPR43. Nat Commun 4:1829. https://doi.org/10.1038/ncomms2852
doi: 10.1038/ncomms2852
pubmed: 23652017
Uemura H, Katsuura-Kamano S, Yamaguchi M et al (2017) Relationships of serum high-sensitivity C-reactive protein and body size with insulin resistance in a Japanese cohort. PLoS One 12(6):e0178672. https://doi.org/10.1371/journal.pone.0178672
doi: 10.1371/journal.pone.0178672
pubmed: 28575103
pmcid: 5456096
Verdam FJ, Fuentes S, de Jonge C et al (2013) Human intestinal microbiota composition is associated with local and systemic inflammation in obesity. Obesity 21(12):E607–E615. https://doi.org/10.1002/oby.20466
doi: 10.1002/oby.20466
pubmed: 23526699
Leiva-Gea I, Sánchez-Alcoholado L, Martín-Tejedor B et al (2018) Gut Microbiota Differs in Composition and Functionality Between Children With Type 1 Diabetes and MODY2 and Healthy Control Subjects: A Case-Control Study. Diabetes Care 41(11):2385–2395. https://doi.org/10.2337/dc18-0253
doi: 10.2337/dc18-0253
pubmed: 30224347
Lambeth SM, Carson T, Lowe J et al (2015) Composition, Diversity and Abundance of Gut Microbiome in Prediabetes and Type 2 Diabetes. J Diabetes Obes 2(3):1–7. https://doi.org/10.15436/2376-0949.15.031
doi: 10.15436/2376-0949.15.031
pubmed: 26756039
pmcid: 4705851
Saravia G, Civeira F, Hurtado-Roca Y et al (2015) Glycated Hemoglobin, Fasting Insulin and the Metabolic Syndrome in Males. Cross-Sectional Analyses of the Aragon Workers’ Health Study Baseline. PLoS One 10(8):e0132244. https://doi.org/10.1371/journal.pone.0132244
doi: 10.1371/journal.pone.0132244
pubmed: 26241903
pmcid: 4524641
Zhang X, Shen D, Fang Z et al (2013) Human gut microbiota changes reveal the progression of glucose intolerance. PLoS One 8(8):e71108. https://doi.org/10.1371/journal.pone.0071108
doi: 10.1371/journal.pone.0071108
pubmed: 24013136
pmcid: 3754967
Lippert K, Kedenko L, Antonielli L et al (2017) Gut microbiota dysbiosis associated with glucose metabolism disorders and the metabolic syndrome in older adults. Benefic Microbes 8(4):545–556. https://doi.org/10.3920/BM2016.0184
doi: 10.3920/BM2016.0184
Egshatyan L, Kashtanova D, Popenko A et al (2016) Gut microbiota and diet in patients with different glucose tolerance. Endocr Connect 5(1):1–9. https://doi.org/10.1530/EC-15-0094
doi: 10.1530/EC-15-0094
pubmed: 26555712
Kashtanova DA, Tkacheva ON, Doudinskaya EN et al (2018) Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study. Microorganisms 6(4):98. https://doi.org/10.3390/microorganisms6040098
doi: 10.3390/microorganisms6040098
pmcid: 6313665
Tuovinen E, Keto J, Nikkilä J, Mättö J, Lähteenmäki K (2013) Cytokine response of human mononuclear cells induced by intestinal Clostridium species. Anaerobe 19:70–76. https://doi.org/10.1016/j.anaerobe.2012.11.002
doi: 10.1016/j.anaerobe.2012.11.002
pubmed: 23168133
Zhu L, Sha L, Li K et al (2020) Dietary flaxseed oil rich in omega-3 suppresses severity of type 2 diabetes mellitus via anti-inflammation and modulating gut microbiota in rats. Lipids Health Dis 19(1):20. https://doi.org/10.1186/s12944-019-1167-4
doi: 10.1186/s12944-019-1167-4
pubmed: 32028957
pmcid: 7006389
Krych Ł, Nielsen DS, Hansen AK, Hansen CHF (2015) Gut microbial markers are associated with diabetes onset, regulatory imbalance, and IFN-γ level in NOD Mice. Gut Microbes 6(2):101–109. https://doi.org/10.1080/19490976.2015.1011876
doi: 10.1080/19490976.2015.1011876
pubmed: 25648687
pmcid: 4615729
Brown CT, Davis-Richardson AG, Giongo A et al (2011) Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes. PLoS One 6(10):e25792. https://doi.org/10.1371/journal.pone.0025792
doi: 10.1371/journal.pone.0025792
pubmed: 22043294
pmcid: 3197175
Mejía-León ME, Petrosino JF, Ajami NJ, Domínguez-Bello MG, de la Barca AMC (2014) Fecal microbiota imbalance in Mexican children with type 1 diabetes. Sci Rep 4(1):3814. https://doi.org/10.1038/srep03814
doi: 10.1038/srep03814
pubmed: 24448554
pmcid: 3898044
Kovatcheva-Datchary P, Nilsson A, Akrami R et al (2015) Dietary Fiber-Induced Improvement in Glucose Metabolism Is Associated with Increased Abundance of Prevotella. Cell Metab 22(6):971–982. https://doi.org/10.1016/j.cmet.2015.10.001
doi: 10.1016/j.cmet.2015.10.001
pubmed: 26552345
Zhu L, Baker SS, Gill C et al (2013) Characterization of gut microbiomes in nonalcoholic steatohepatitis (NASH) patients: a connection between endogenous alcohol and NASH. Hepatology 57(2):601–609. https://doi.org/10.1002/hep.26093
doi: 10.1002/hep.26093
pubmed: 23055155
Hu H-J, Park S-G, Jang HB et al (2015) Obesity Alters the Microbial Community Profile in Korean Adolescents. PLoS One 10(7):e0134333. https://doi.org/10.1371/journal.pone.0134333
doi: 10.1371/journal.pone.0134333
pubmed: 26230509
pmcid: 4521691
Leite AZ, de Campos Rodrigues N, Gonzaga MI et al (2017) Detection of Increased Plasma Interleukin-6 Levels and Prevalence of Prevotella copri and Bacteroides vulgatus in the Feces of Type 2 Diabetes Patients. Front Immunol 8:1107. https://doi.org/10.3389/fimmu.2017.01107
doi: 10.3389/fimmu.2017.01107
pubmed: 28966614
pmcid: 5605568
Iljazovic A, Roy U, Gálvez EJC et al (2021) Perturbation of the gut microbiome by Prevotella spp. enhances host susceptibility to mucosal inflammation. Mucosal Immunol 14(1):113–124. https://doi.org/10.1038/s41385-020-0296-4
doi: 10.1038/s41385-020-0296-4
pubmed: 32433514