Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery. / Lappa, Dimitra; Meijnikman, Abraham S.; Krautkramer, Kimberly A.; Olsson, Lisa M.; Aydin, Ömrüm; Van Rijswijk, Anne Sophie; Acherman, Yair I.Z.; De Brauw, Maurits L.; Tremaroli, Valentina; Olofsson, Louise E.; Lundqvist, Annika; Hjorth, Siv A.; Ji, Boyang; Gerdes, Victor E.A.; Groen, Albert K.; Schwartz, Thue W.; Nieuwdorp, Max; Bäckhed, Fredrik; Nielsen, Jens.

In: PLoS ONE, Vol. 18, No. 3, e0279335, 2023.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Lappa, D, Meijnikman, AS, Krautkramer, KA, Olsson, LM, Aydin, Ö, Van Rijswijk, AS, Acherman, YIZ, De Brauw, ML, Tremaroli, V, Olofsson, LE, Lundqvist, A, Hjorth, SA, Ji, B, Gerdes, VEA, Groen, AK, Schwartz, TW, Nieuwdorp, M, Bäckhed, F & Nielsen, J 2023, 'Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery', PLoS ONE, vol. 18, no. 3, e0279335. https://doi.org/10.1371/journal.pone.0279335

APA

Lappa, D., Meijnikman, A. S., Krautkramer, K. A., Olsson, L. M., Aydin, Ö., Van Rijswijk, A. S., Acherman, Y. I. Z., De Brauw, M. L., Tremaroli, V., Olofsson, L. E., Lundqvist, A., Hjorth, S. A., Ji, B., Gerdes, V. E. A., Groen, A. K., Schwartz, T. W., Nieuwdorp, M., Bäckhed, F., & Nielsen, J. (2023). Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery. PLoS ONE, 18(3), [e0279335]. https://doi.org/10.1371/journal.pone.0279335

Vancouver

Lappa D, Meijnikman AS, Krautkramer KA, Olsson LM, Aydin Ö, Van Rijswijk AS et al. Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery. PLoS ONE. 2023;18(3). e0279335. https://doi.org/10.1371/journal.pone.0279335

Author

Lappa, Dimitra ; Meijnikman, Abraham S. ; Krautkramer, Kimberly A. ; Olsson, Lisa M. ; Aydin, Ömrüm ; Van Rijswijk, Anne Sophie ; Acherman, Yair I.Z. ; De Brauw, Maurits L. ; Tremaroli, Valentina ; Olofsson, Louise E. ; Lundqvist, Annika ; Hjorth, Siv A. ; Ji, Boyang ; Gerdes, Victor E.A. ; Groen, Albert K. ; Schwartz, Thue W. ; Nieuwdorp, Max ; Bäckhed, Fredrik ; Nielsen, Jens. / Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery. In: PLoS ONE. 2023 ; Vol. 18, No. 3.

Bibtex

@article{8eead058aaab4aa5b03daa7d94098bb2,
title = "Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery",
abstract = "Weight loss through bariatric surgery is efficient for treatment or prevention of obesity related diseases such as type 2 diabetes and cardiovascular disease. Long term weight loss response does, however, vary among patients undergoing surgery. Thus, it is difficult to identify predictive markers while most obese individuals have one or more comorbidities. To overcome such challenges, an in-depth multiple omics analyses including fasting peripheral plasma metabolome, fecal metagenome as well as liver, jejunum, and adipose tissue transcriptome were performed for 106 individuals undergoing bariatric surgery. Machine leaning was applied to explore the metabolic differences in individuals and evaluate if metabolism-based patients{\textquoteright} stratification is related to their weight loss responses to bariatric surgery. Using Self-Organizing Maps (SOMs) to analyze the plasma metabolome, we identified five distinct metabotypes, which were differentially enriched for KEGG pathways related to immune functions, fatty acid metabolism, protein-signaling, and obesity pathogenesis. The gut metagenome of the most heavily medicated metabotypes, treated simultaneously for multiple cardiometabolic comorbidities, was significantly enriched in Prevotella and Lactobacillus species. This unbiased stratification into SOM-defined metabotypes identified signatures for each metabolic phenotype and we found that the different metabotypes respond differently to bariatric surgery in terms of weight loss after 12 months. An integrative framework that utilizes SOMs and omics integration was developed for stratifying a heterogeneous bariatric surgery cohort. The multiple omics datasets described in this study reveal that the metabotypes are characterized by a concrete metabolic status and different responses in weight loss and adipose tissue reduction over time. Our study thus opens a path to enable patient stratification and hereby allow for improved clinical treatments.",
author = "Dimitra Lappa and Meijnikman, {Abraham S.} and Krautkramer, {Kimberly A.} and Olsson, {Lisa M.} and {\"O}mr{\"u}m Aydin and {Van Rijswijk}, {Anne Sophie} and Acherman, {Yair I.Z.} and {De Brauw}, {Maurits L.} and Valentina Tremaroli and Olofsson, {Louise E.} and Annika Lundqvist and Hjorth, {Siv A.} and Boyang Ji and Gerdes, {Victor E.A.} and Groen, {Albert K.} and Schwartz, {Thue W.} and Max Nieuwdorp and Fredrik B{\"a}ckhed and Jens Nielsen",
note = "Publisher Copyright: {\textcopyright} 2023 Lappa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2023",
doi = "10.1371/journal.pone.0279335",
language = "English",
volume = "18",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "3",

}

RIS

TY - JOUR

T1 - Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery

AU - Lappa, Dimitra

AU - Meijnikman, Abraham S.

AU - Krautkramer, Kimberly A.

AU - Olsson, Lisa M.

AU - Aydin, Ömrüm

AU - Van Rijswijk, Anne Sophie

AU - Acherman, Yair I.Z.

AU - De Brauw, Maurits L.

AU - Tremaroli, Valentina

AU - Olofsson, Louise E.

AU - Lundqvist, Annika

AU - Hjorth, Siv A.

AU - Ji, Boyang

AU - Gerdes, Victor E.A.

AU - Groen, Albert K.

AU - Schwartz, Thue W.

AU - Nieuwdorp, Max

AU - Bäckhed, Fredrik

AU - Nielsen, Jens

N1 - Publisher Copyright: © 2023 Lappa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2023

Y1 - 2023

N2 - Weight loss through bariatric surgery is efficient for treatment or prevention of obesity related diseases such as type 2 diabetes and cardiovascular disease. Long term weight loss response does, however, vary among patients undergoing surgery. Thus, it is difficult to identify predictive markers while most obese individuals have one or more comorbidities. To overcome such challenges, an in-depth multiple omics analyses including fasting peripheral plasma metabolome, fecal metagenome as well as liver, jejunum, and adipose tissue transcriptome were performed for 106 individuals undergoing bariatric surgery. Machine leaning was applied to explore the metabolic differences in individuals and evaluate if metabolism-based patients’ stratification is related to their weight loss responses to bariatric surgery. Using Self-Organizing Maps (SOMs) to analyze the plasma metabolome, we identified five distinct metabotypes, which were differentially enriched for KEGG pathways related to immune functions, fatty acid metabolism, protein-signaling, and obesity pathogenesis. The gut metagenome of the most heavily medicated metabotypes, treated simultaneously for multiple cardiometabolic comorbidities, was significantly enriched in Prevotella and Lactobacillus species. This unbiased stratification into SOM-defined metabotypes identified signatures for each metabolic phenotype and we found that the different metabotypes respond differently to bariatric surgery in terms of weight loss after 12 months. An integrative framework that utilizes SOMs and omics integration was developed for stratifying a heterogeneous bariatric surgery cohort. The multiple omics datasets described in this study reveal that the metabotypes are characterized by a concrete metabolic status and different responses in weight loss and adipose tissue reduction over time. Our study thus opens a path to enable patient stratification and hereby allow for improved clinical treatments.

AB - Weight loss through bariatric surgery is efficient for treatment or prevention of obesity related diseases such as type 2 diabetes and cardiovascular disease. Long term weight loss response does, however, vary among patients undergoing surgery. Thus, it is difficult to identify predictive markers while most obese individuals have one or more comorbidities. To overcome such challenges, an in-depth multiple omics analyses including fasting peripheral plasma metabolome, fecal metagenome as well as liver, jejunum, and adipose tissue transcriptome were performed for 106 individuals undergoing bariatric surgery. Machine leaning was applied to explore the metabolic differences in individuals and evaluate if metabolism-based patients’ stratification is related to their weight loss responses to bariatric surgery. Using Self-Organizing Maps (SOMs) to analyze the plasma metabolome, we identified five distinct metabotypes, which were differentially enriched for KEGG pathways related to immune functions, fatty acid metabolism, protein-signaling, and obesity pathogenesis. The gut metagenome of the most heavily medicated metabotypes, treated simultaneously for multiple cardiometabolic comorbidities, was significantly enriched in Prevotella and Lactobacillus species. This unbiased stratification into SOM-defined metabotypes identified signatures for each metabolic phenotype and we found that the different metabotypes respond differently to bariatric surgery in terms of weight loss after 12 months. An integrative framework that utilizes SOMs and omics integration was developed for stratifying a heterogeneous bariatric surgery cohort. The multiple omics datasets described in this study reveal that the metabotypes are characterized by a concrete metabolic status and different responses in weight loss and adipose tissue reduction over time. Our study thus opens a path to enable patient stratification and hereby allow for improved clinical treatments.

U2 - 10.1371/journal.pone.0279335

DO - 10.1371/journal.pone.0279335

M3 - Journal article

C2 - 36862673

AN - SCOPUS:85149342098

VL - 18

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 3

M1 - e0279335

ER -

ID: 339994132