Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Sandra Reitmeier; Silke Kiessling; Thomas Clavel; Markus List; Eduardo L. Almeida; Tarini S. Ghosh; Klaus Neuhaus; Harald Grallert; Jakob Linseisen; Thomas Skurk; Beate Brandl; Taylor A. Breuninger; Martina Troll; Wolfgang Rathmann; Birgit Linkohr; Hans Hauner; Matthias Laudes; Andre Franke; Caroline I. Le Roy; Jordana T. Bell; Tim Spector; Jan Baumbach; Paul W. O'Toole; Annette Peters; Dirk Haller

doi:10.1016/j.chom.2020.06.004

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Sandra Reitmeier, Silke Kiessling, Thomas Clavel, Markus List, Eduardo L. Almeida, Tarini S. Ghosh, Klaus Neuhaus, Harald Grallert, Jakob Linseisen, Thomas Skurk, Beate Brandl, Taylor A. Breuninger, Martina Troll, Wolfgang Rathmann, Birgit Linkohr, Hans Hauner, Matthias Laudes, Andre Franke, Caroline I. Le Roy, Jordana T. BellTim Spector, Jan Baumbach, Paul W. O'Toole, Annette Peters, Dirk Haller^*

^*Corresponding author for this work

Twin Research & Genetic Epidemiology

Research output: Contribution to journal › Article › peer-review

184 Citations (Scopus)

Abstract

Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases. Reitmeier et al. show that specific gut microbes exhibit rhythmic oscillations in relative abundance and identified taxa with disrupted rhythmicity in individuals with type 2 diabetes (T2D). This arrhythmic signature contributed to the classification and prediction of T2D, suggesting functional links between circadian rhythmicity and the microbiome in metabolic diseases.

Original language	English
Pages (from-to)	258-272.e6
Journal	Cell Host and Microbe
Volume	28
Issue number	2
DOIs	https://doi.org/10.1016/j.chom.2020.06.004
Publication status	Published - 12 Aug 2020

Keywords

amplicon sequencing
circadian rhythms
diurnal oscillations
human intestinal microbiota
machine learning
metagenomics
obesity
population-based cohorts
prediction
type 2 diabetes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.chom.2020.06.004

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Reitmeier, S., Kiessling, S., Clavel, T., List, M., Almeida, E. L., Ghosh, T. S., Neuhaus, K., Grallert, H., Linseisen, J., Skurk, T., Brandl, B., Breuninger, T. A., Troll, M., Rathmann, W., Linkohr, B., Hauner, H., Laudes, M., Franke, A., Le Roy, C. I., ... Haller, D. (2020). Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes. Cell Host and Microbe, 28(2), 258-272.e6. https://doi.org/10.1016/j.chom.2020.06.004

@article{c5b00e0e1911453aad8baaf000086621,

title = "Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes",

abstract = "Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases. Reitmeier et al. show that specific gut microbes exhibit rhythmic oscillations in relative abundance and identified taxa with disrupted rhythmicity in individuals with type 2 diabetes (T2D). This arrhythmic signature contributed to the classification and prediction of T2D, suggesting functional links between circadian rhythmicity and the microbiome in metabolic diseases.",

keywords = "amplicon sequencing, circadian rhythms, diurnal oscillations, human intestinal microbiota, machine learning, metagenomics, obesity, population-based cohorts, prediction, type 2 diabetes",

author = "Sandra Reitmeier and Silke Kiessling and Thomas Clavel and Markus List and Almeida, {Eduardo L.} and Ghosh, {Tarini S.} and Klaus Neuhaus and Harald Grallert and Jakob Linseisen and Thomas Skurk and Beate Brandl and Breuninger, {Taylor A.} and Martina Troll and Wolfgang Rathmann and Birgit Linkohr and Hans Hauner and Matthias Laudes and Andre Franke and {Le Roy}, {Caroline I.} and Bell, {Jordana T.} and Tim Spector and Jan Baumbach and O'Toole, {Paul W.} and Annette Peters and Dirk Haller",

year = "2020",

month = aug,

day = "12",

doi = "10.1016/j.chom.2020.06.004",

language = "English",

volume = "28",

pages = "258--272.e6",

journal = "Cell Host and Microbe",

issn = "1931-3128",

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Reitmeier, S, Kiessling, S, Clavel, T, List, M, Almeida, EL, Ghosh, TS, Neuhaus, K, Grallert, H, Linseisen, J, Skurk, T, Brandl, B, Breuninger, TA, Troll, M, Rathmann, W, Linkohr, B, Hauner, H, Laudes, M, Franke, A, Le Roy, CI , Bell, JT , Spector, T, Baumbach, J, O'Toole, PW, Peters, A & Haller, D 2020, 'Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes', Cell Host and Microbe, vol. 28, no. 2, pp. 258-272.e6. https://doi.org/10.1016/j.chom.2020.06.004

TY - JOUR

T1 - Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

AU - Reitmeier, Sandra

AU - Kiessling, Silke

AU - Clavel, Thomas

AU - List, Markus

AU - Almeida, Eduardo L.

AU - Ghosh, Tarini S.

AU - Neuhaus, Klaus

AU - Grallert, Harald

AU - Linseisen, Jakob

AU - Skurk, Thomas

AU - Brandl, Beate

AU - Breuninger, Taylor A.

AU - Troll, Martina

AU - Rathmann, Wolfgang

AU - Linkohr, Birgit

AU - Hauner, Hans

AU - Laudes, Matthias

AU - Franke, Andre

AU - Le Roy, Caroline I.

AU - Bell, Jordana T.

AU - Spector, Tim

AU - Baumbach, Jan

AU - O'Toole, Paul W.

AU - Peters, Annette

AU - Haller, Dirk

PY - 2020/8/12

Y1 - 2020/8/12

N2 - Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases. Reitmeier et al. show that specific gut microbes exhibit rhythmic oscillations in relative abundance and identified taxa with disrupted rhythmicity in individuals with type 2 diabetes (T2D). This arrhythmic signature contributed to the classification and prediction of T2D, suggesting functional links between circadian rhythmicity and the microbiome in metabolic diseases.

AB - Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases. Reitmeier et al. show that specific gut microbes exhibit rhythmic oscillations in relative abundance and identified taxa with disrupted rhythmicity in individuals with type 2 diabetes (T2D). This arrhythmic signature contributed to the classification and prediction of T2D, suggesting functional links between circadian rhythmicity and the microbiome in metabolic diseases.

KW - amplicon sequencing

KW - circadian rhythms

KW - diurnal oscillations

KW - human intestinal microbiota

KW - machine learning

KW - metagenomics

KW - obesity

KW - population-based cohorts

KW - prediction

KW - type 2 diabetes

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U2 - 10.1016/j.chom.2020.06.004

DO - 10.1016/j.chom.2020.06.004

M3 - Article

C2 - 32619440

AN - SCOPUS:85087971140

SN - 1931-3128

VL - 28

SP - 258-272.e6

JO - Cell Host and Microbe

JF - Cell Host and Microbe

IS - 2

ER -

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Abstract

Keywords

UN SDGs

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