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Author Correction: Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Authors:
Rosa Lundbye Allesøe
Rosa Lundbye Allesøe
Rosa Lundbye Allesøe
  • This person is not on ResearchGate, or hasn't claimed this research yet.
Agnete Troen Lundgaard
Agnete Troen Lundgaard
Agnete Troen Lundgaard
  • This person is not on ResearchGate, or hasn't claimed this research yet.
Ricardo Alexis Hernández Medina at Instituto Tecnológico de Tlalnepantla
Ricardo Alexis Hernández Medina
Alejandro Aguayo at University of Copenhagen
Alejandro Aguayo
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nature biotechnology
Corrections & amendments
Author Correction: Discovery of drug–omics associations
in type 2 diabetes with generative deep-learning models
Rosa Lundbye Allesøe, Agnete Troen Lundgaard   ,
Ricardo Hernández Medina   , Alejandro Aguayo-Orozco, Joachim Johansen   ,
Jakob Nybo Nissen, Caroline Brorsson, Gianluca Mazzoni, Lili Niu   ,
Jorge Hernansanz Biel   , Cristina Leal Rodríguez   , Valentas Brasas,
Henry Webel, Michael Eriksen Benros   , Anders Gorm Pedersen   ,
Piotr Jaroslaw Chmura, Ulrik Plesner Jacobsen   , Andrea Mari,
Robert Koivula   , Anubha Mahajan, Ana Vinuela   , Juan Fernandez Tajes,
Sapna Sharma, Mark Haid   , Mun-Gwan Hong   , Petra B. Musholt,
Federico De Masi, Josef Vogt, Helle Krogh Pedersen, Valborg Gudmundsdottir,
Angus Jones, Gwen Kennedy   , Jimmy Bell, E. Louise Thomas   , Gary Frost   ,
Henrik Thomsen, Elizaveta Hansen, Tue Haldor Hansen   , Henrik Vestergaard,
Mirthe Muilwijk, Marieke T. Blom, Leen M. ‘t Hart, Francois Pattou,
Violeta Raverdy, Soren Brage, Tarja Kokkola, Alison Heggie, Donna McEvoy,
Miranda Mourby, Jane Kaye   , Andrew Hattersley   , Timothy McDonald,
Martin Ridderstråle   , Mark Walker, Ian Forgie, Giuseppe N. Giordano,
Imre Pavo, Hartmut Ruetten, Oluf Pedersen   , Torben Hansen   ,
Emmanouil Dermitzakis, Paul W. Franks, Jochen M. Schwenk   , Jerzy Adamski,
Mark I. McCarthy, Ewan Pearson, Karina Banasik, Simon Rasmussen   ,
Søren Brunak    & IMI DIRECT Consortium*
In the version of this article initially published, Cristina Leal Rodríguez (Novo Nordisk Founda-
tion Center for Protein Research, Faculty of Health and Medical Sciences, University of Copen-
hagen, Copenhagen, Denmark) was omitted from the author list. The error has been corrected
in the HTML and PDF versions of the article.
*Lists of authors and their afiliations appear online.
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© The Author(s) 2023
Correction to: Nature Biotechnology https://
doi.org/10.1038/s41587-022-01520-x.
Published online 2 January 2023.
https://doi.org/10.1038/s41587-023-01805-9
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... We also observed trends in metabolic pathways: a decrease in aminoacyl tRNA biosynthesis, metabolism of glycine, serine, and threonine, biosynthesis of valine, leucine, and isoleucine, and lysine degradation pathways. Aminoacyl tRNA biosynthesis is involved in the synthesis of amino acids as well as in a variety of metabolic processes such as protein synthesis, hormone synthesis, and glycolipid metabolism (28).Roas et al. found a significant enrichment of metabolites associated with aminoacyl-tRNA biosynthesis after the use of metformin (29), and in our study we found that the metabolism of a wide variety of amino acids centered on aminoacyl-tRNA biosynthesis mainly including amino acids such as glycine, serine, threonine, methionine, lysine, alanine, isoleucine, leucine, and tyrosine, and that a decrease in the metabolic pathways of glycine, serine, and threonine indicated an increase in the levels of glycine, serine, and threonine, which was in agreement with the previous study (30), in which glycine, serine, and threonine were associated with an improvement in insulin sensitivity (31). Previous studies have shown that changes in plasma glycine may be one of the biomarkers of T2DM (32), and Chen et al. found in their study that insulin secretion was higher in diabetic rats taking glycine compared to diabetic rats not taking glycine (33). ...
Effect of oral metformin on gut microbiota characteristics and metabolite fractions in normal-weight type 2 diabetic mellitus patients
Article
Full-text available
  • Aug 2024
Background and aims To analyze the effect of oral metformin on changes in gut microbiota characteristics and metabolite composition in normal weight type 2 diabetic patients. Methods T2DM patients in the cross-sectional study were given metformin for 12 weeks. Patients with unmedicated T2DM were used as a control group to observe the metrics of T2DM patients treated with metformin regimen. 16S rDNA high-throughput gene sequencing of fecal gut microbiota of the study subjects was performed by llumina NovaSeq6000 platform. Targeted macro-metabolomics was performed on 14 cases of each of the gut microbiota metabolites of the study subjects using UPLC-MS/MS technology. Correlations between the characteristics of the gut microbiota and its metabolites, basic human parameters, glycolipid metabolism indicators, and inflammatory factors were analyzed using spearman analysis. Results Glycolipid metabolism indexes and inflammatory factors were higher in normal-weight T2DM patients than in the healthy population (P<0.05), but body weight, BMI, waist circumference, and inflammatory factor concentrations were lower in normal-weight T2DM patients than in obese T2DM patients (P<0.05). Treatment with metformin in T2DM patients improved glycolipid metabolism, but the recovery of glycolipid metabolism was more pronounced in obese T2DM patients. None of the differences in α-diversity indexes were statistically significant (P>0.05), and the differences in β-diversity were statistically significant (P <0.05). Community diversity and species richness recovered after metformin intervention compared to before, and were closer to the healthy population. We found that Anaerostipes/Xylose/Ribulose/Xylulose may play an important role in the treatment of normal-weight T2DM with metformin by improving glycemic lipids and reducing inflammation. And Metformin may play a role in obese T2DM through Romboutsia, medium-chain fatty acids (octanoic acid, decanoic acid, and dodecanoic acid). Conclusion Gut microbial dysbiosis and metabolic disorders were closely related to glucose-lipid metabolism and systemic inflammatory response in normal-weight T2DM patients. Metformin treatment improved glucose metabolism levels, systemic inflammation levels in T2DM patients, closer to the state of healthy population. This effect may be mediated by influencing the gut microbiota and microbial host co-metabolites, mainly associated with Anaerostipes and xylose/Ribulose/Xylulose. Metformin may exert its effects through different pathways in normal-weight versus obese T2DM patients.
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