Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals

Katri Korpela, Harry J Flint, Alexandra M Johnstone, Jenni Lappi, Kaisa Poutanen, Evelyne Dewulf, Nathalie Delzenne, Willem M de Vos, Anne Salonen

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Abstract

BACKGROUND: Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host.

METHODOLOGY: Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set - test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters.

PRINCIPAL FINDINGS: Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77-1; predicted vs. observed correlation  =  0.67-0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health.

CONCLUSION: This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of microbiota signatures for personalized nutrition.

Original languageEnglish
Article numbere90702
Number of pages10
JournalPloS ONE
Volume9
Issue number3
DOIs
Publication statusPublished - 6 Mar 2014

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Microbiota
intestinal microorganisms
Health
Nutrition
Area Under Curve
Cholesterol
cholesterol
Biomarkers
Microarrays
Metabolism
Belgium
Finland
blood serum
Gastrointestinal Microbiome
microbiome
Logistics
Blood
United Kingdom
Linear Models
biomarkers

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Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals. / Korpela, Katri; Flint, Harry J; Johnstone, Alexandra M; Lappi, Jenni; Poutanen, Kaisa; Dewulf, Evelyne; Delzenne, Nathalie; de Vos, Willem M; Salonen, Anne.

In: PloS ONE, Vol. 9, No. 3, e90702, 06.03.2014.

Research output: Contribution to journalArticle

Korpela, K, Flint, HJ, Johnstone, AM, Lappi, J, Poutanen, K, Dewulf, E, Delzenne, N, de Vos, WM & Salonen, A 2014, 'Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals', PloS ONE, vol. 9, no. 3, e90702. https://doi.org/10.1371/journal.pone.0090702
Korpela, Katri ; Flint, Harry J ; Johnstone, Alexandra M ; Lappi, Jenni ; Poutanen, Kaisa ; Dewulf, Evelyne ; Delzenne, Nathalie ; de Vos, Willem M ; Salonen, Anne. / Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals. In: PloS ONE. 2014 ; Vol. 9, No. 3.
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abstract = "BACKGROUND: Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host.METHODOLOGY: Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set - test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters.PRINCIPAL FINDINGS: Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77-1; predicted vs. observed correlation  =  0.67-0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health.CONCLUSION: This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of microbiota signatures for personalized nutrition.",
author = "Katri Korpela and Flint, {Harry J} and Johnstone, {Alexandra M} and Jenni Lappi and Kaisa Poutanen and Evelyne Dewulf and Nathalie Delzenne and {de Vos}, {Willem M} and Anne Salonen",
note = "In{\'e}s Mart{\'i}nez and Jens Walter (Department of Food Science and Technology, University of Nebraska, USA) are acknowledged for sharing their 454-sequencing data. Jarmo Ritari (Department of Veterinary Biosciences, University of Helsinki, Finland) helped in the analysis of sequencing data. Jean-Paul Thissen (IREC/ST Luc Hospital, Universit{\'e} catholique de Louvain, Belgium) is acknowledged for the study protocol and follow-up of patients in study C. HF and AJ acknowledge support from the Scottish Government Food, Land and People program.",
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T1 - Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals

AU - Korpela, Katri

AU - Flint, Harry J

AU - Johnstone, Alexandra M

AU - Lappi, Jenni

AU - Poutanen, Kaisa

AU - Dewulf, Evelyne

AU - Delzenne, Nathalie

AU - de Vos, Willem M

AU - Salonen, Anne

N1 - Inés Martínez and Jens Walter (Department of Food Science and Technology, University of Nebraska, USA) are acknowledged for sharing their 454-sequencing data. Jarmo Ritari (Department of Veterinary Biosciences, University of Helsinki, Finland) helped in the analysis of sequencing data. Jean-Paul Thissen (IREC/ST Luc Hospital, Université catholique de Louvain, Belgium) is acknowledged for the study protocol and follow-up of patients in study C. HF and AJ acknowledge support from the Scottish Government Food, Land and People program.

PY - 2014/3/6

Y1 - 2014/3/6

N2 - BACKGROUND: Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host.METHODOLOGY: Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set - test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters.PRINCIPAL FINDINGS: Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77-1; predicted vs. observed correlation  =  0.67-0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health.CONCLUSION: This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of microbiota signatures for personalized nutrition.

AB - BACKGROUND: Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host.METHODOLOGY: Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set - test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters.PRINCIPAL FINDINGS: Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77-1; predicted vs. observed correlation  =  0.67-0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health.CONCLUSION: This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of microbiota signatures for personalized nutrition.

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