Multiomics signatures of type 1 diabetes with and without albuminuria

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Multiomics signatures of type 1 diabetes with and without albuminuria. / Clos-Garcia, Marc; Ahluwalia, Tarunveer S.; Winther, Signe A.; Henriksen, Peter; Ali, Mina; Fan, Yong; Stankevic, Evelina; Lyu, Liwei; Vogt, Josef K.; Hansen, Torben; Legido-Quigley, Cristina; Rossing, Peter; Pedersen, Oluf.

I: Frontiers in Endocrinology, Bind 13, 1015557, 2022.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Clos-Garcia, M, Ahluwalia, TS, Winther, SA, Henriksen, P, Ali, M, Fan, Y, Stankevic, E, Lyu, L, Vogt, JK, Hansen, T, Legido-Quigley, C, Rossing, P & Pedersen, O 2022, 'Multiomics signatures of type 1 diabetes with and without albuminuria', Frontiers in Endocrinology, bind 13, 1015557. https://doi.org/10.3389/fendo.2022.1015557

APA

Clos-Garcia, M., Ahluwalia, T. S., Winther, S. A., Henriksen, P., Ali, M., Fan, Y., Stankevic, E., Lyu, L., Vogt, J. K., Hansen, T., Legido-Quigley, C., Rossing, P., & Pedersen, O. (2022). Multiomics signatures of type 1 diabetes with and without albuminuria. Frontiers in Endocrinology, 13, [1015557]. https://doi.org/10.3389/fendo.2022.1015557

Vancouver

Clos-Garcia M, Ahluwalia TS, Winther SA, Henriksen P, Ali M, Fan Y o.a. Multiomics signatures of type 1 diabetes with and without albuminuria. Frontiers in Endocrinology. 2022;13. 1015557. https://doi.org/10.3389/fendo.2022.1015557

Author

Clos-Garcia, Marc ; Ahluwalia, Tarunveer S. ; Winther, Signe A. ; Henriksen, Peter ; Ali, Mina ; Fan, Yong ; Stankevic, Evelina ; Lyu, Liwei ; Vogt, Josef K. ; Hansen, Torben ; Legido-Quigley, Cristina ; Rossing, Peter ; Pedersen, Oluf. / Multiomics signatures of type 1 diabetes with and without albuminuria. I: Frontiers in Endocrinology. 2022 ; Bind 13.

Bibtex

@article{ee782cb568e14ecfbe6196b75b20b00c,
title = "Multiomics signatures of type 1 diabetes with and without albuminuria",
abstract = "Aims/hypothesis: To identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role. Methods: One hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool. Results: Measures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals. Conclusions: Individuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.",
keywords = "albuminuria, lipidomics, metabolomics, microbiome, multiomics, phageome, type 1 diabetes",
author = "Marc Clos-Garcia and Ahluwalia, {Tarunveer S.} and Winther, {Signe A.} and Peter Henriksen and Mina Ali and Yong Fan and Evelina Stankevic and Liwei Lyu and Vogt, {Josef K.} and Torben Hansen and Cristina Legido-Quigley and Peter Rossing and Oluf Pedersen",
note = "Publisher Copyright: Copyright {\textcopyright} 2022 Clos-Garcia, Ahluwalia, Winther, Henriksen, Ali, Fan, Stankevic, Lyu, Vogt, Hansen, Legido-Quigley, Rossing and Pedersen.",
year = "2022",
doi = "10.3389/fendo.2022.1015557",
language = "English",
volume = "13",
journal = "Frontiers in Endocrinology",
issn = "1664-2392",
publisher = "Frontiers Media S.A.",

}

RIS

TY - JOUR

T1 - Multiomics signatures of type 1 diabetes with and without albuminuria

AU - Clos-Garcia, Marc

AU - Ahluwalia, Tarunveer S.

AU - Winther, Signe A.

AU - Henriksen, Peter

AU - Ali, Mina

AU - Fan, Yong

AU - Stankevic, Evelina

AU - Lyu, Liwei

AU - Vogt, Josef K.

AU - Hansen, Torben

AU - Legido-Quigley, Cristina

AU - Rossing, Peter

AU - Pedersen, Oluf

N1 - Publisher Copyright: Copyright © 2022 Clos-Garcia, Ahluwalia, Winther, Henriksen, Ali, Fan, Stankevic, Lyu, Vogt, Hansen, Legido-Quigley, Rossing and Pedersen.

PY - 2022

Y1 - 2022

N2 - Aims/hypothesis: To identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role. Methods: One hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool. Results: Measures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals. Conclusions: Individuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.

AB - Aims/hypothesis: To identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role. Methods: One hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool. Results: Measures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals. Conclusions: Individuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.

KW - albuminuria

KW - lipidomics

KW - metabolomics

KW - microbiome

KW - multiomics

KW - phageome

KW - type 1 diabetes

U2 - 10.3389/fendo.2022.1015557

DO - 10.3389/fendo.2022.1015557

M3 - Journal article

C2 - 36531462

AN - SCOPUS:85144053192

VL - 13

JO - Frontiers in Endocrinology

JF - Frontiers in Endocrinology

SN - 1664-2392

M1 - 1015557

ER -

ID: 330196105