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 tidsskrift › Tidsskriftartikel › fagfællebedømt
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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