Identification of biomarkers for glycaemic deterioration in type 2 diabetes

Roderick C. Slieker; Louise A. Donnelly; Elina Akalestou; Livia Lopez-Noriega; Rana Melhem; Ayşim Güneş; Frederic Abou Azar; Alexander Efanov; Eleni Georgiadou; Hermine Muniangi-Muhitu; Mahsa Sheikh; Giuseppe N. Giordano; Mikael Åkerlund; Emma Ahlqvist; Ashfaq Ali; Karina Banasik; S. ren Brunak; Marko Barovic; Gerard A. Bouland; Frédéric Burdet; Mickaël Canouil; Iulian Dragan; Petra J. M. Elders; Celine Fernandez; Andreas Festa; Hugo Fitipaldi; Phillippe Froguel; Valborg Gudmundsdottir; Vilmundur Gudnason; Mathias J. Gerl; Amber A. van der Heijden; Lori L. Jennings; Michael K. Hansen; Min Kim; Isabelle Leclerc; Christian Klose; Dmitry Kuznetsov; Dina Mansour Aly; Florence Mehl; Diana Marek; Olle Melander; Anne Niknejad; Filip Ottosson; Imre Pavo; Kevin Duffin; Samreen K. Syed; Janice L. Shaw; Over Cabrera; Timothy J. Pullen; Kai Simons; Michele Solimena; Tommi Suvitaival; Asger Wretlind; Peter Rossing; Valeriya Lyssenko; Cristina Legido Quigley; Leif Groop; Bernard Thorens; Paul W. Franks; Gareth E. Lim; Jennifer Estall; Mark Ibberson; Joline W. J. Beulens; Leen M. ’t Hart; Ewan R. Pearson; Guy A. Rutter

doi:https://doi.org/10.1038/s41467-023-38148-7

Identification of biomarkers for glycaemic deterioration in type 2 diabetes

Roderick C. Slieker, Louise A. Donnelly, Elina Akalestou, Livia Lopez-Noriega, Rana Melhem, Ayşim Güneş, Frederic Abou Azar, Alexander Efanov, Eleni Georgiadou, Hermine Muniangi-Muhitu, Mahsa Sheikh, Giuseppe N. Giordano, Mikael Åkerlund, Emma Ahlqvist, Ashfaq Ali, Karina Banasik, S. ren Brunak, Marko Barovic, Gerard A. Bouland, Frédéric BurdetMickaël Canouil, Iulian Dragan, Petra J. M. Elders, Celine Fernandez, Andreas Festa, Hugo Fitipaldi, Phillippe Froguel, Valborg Gudmundsdottir, Vilmundur Gudnason, Mathias J. Gerl, Amber A. van der Heijden, Lori L. Jennings, Michael K. Hansen, Min Kim, Isabelle Leclerc, Christian Klose, Dmitry Kuznetsov, Dina Mansour Aly, Florence Mehl, Diana Marek, Olle Melander, Anne Niknejad, Filip Ottosson, Imre Pavo, Kevin Duffin, Samreen K. Syed, Janice L. Shaw, Over Cabrera, Timothy J. Pullen, Kai Simons, Michele Solimena, Tommi Suvitaival, Asger Wretlind, Peter Rossing, Valeriya Lyssenko, Cristina Legido Quigley, Leif Groop, Bernard Thorens, Paul W. Franks, Gareth E. Lim, Jennifer Estall, Mark Ibberson, Joline W. J. Beulens, Leen M. ’t Hart, Ewan R. Pearson, Guy A. Rutter

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Original language	English
Article number	2533
Journal	Nature communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-38148-7
Publication status	Published - 1 Dec 2023

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https://doi.org/10.1038/s41467-023-38148-7

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Slieker, R. C., Donnelly, L. A., Akalestou, E., Lopez-Noriega, L., Melhem, R., Güneş, A., Abou Azar, F., Efanov, A., Georgiadou, E., Muniangi-Muhitu, H., Sheikh, M., Giordano, G. N., Åkerlund, M., Ahlqvist, E., Ali, A., Banasik, K., Brunak, S. R., Barovic, M., Bouland, G. A., ... Rutter, G. A. (2023). Identification of biomarkers for glycaemic deterioration in type 2 diabetes. Nature communications, 14(1), Article 2533. https://doi.org/10.1038/s41467-023-38148-7

@article{e84e65bf78c449d38937228939554abe,

title = "Identification of biomarkers for glycaemic deterioration in type 2 diabetes",

abstract = "We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.",

author = "Slieker, {Roderick C.} and Donnelly, {Louise A.} and Elina Akalestou and Livia Lopez-Noriega and Rana Melhem and Ay{\c s}im G{\"u}ne{\c s} and {Abou Azar}, Frederic and Alexander Efanov and Eleni Georgiadou and Hermine Muniangi-Muhitu and Mahsa Sheikh and Giordano, {Giuseppe N.} and Mikael {\AA}kerlund and Emma Ahlqvist and Ashfaq Ali and Karina Banasik and Brunak, {S. ren} and Marko Barovic and Bouland, {Gerard A.} and Fr{\'e}d{\'e}ric Burdet and Micka{\"e}l Canouil and Iulian Dragan and Elders, {Petra J. M.} and Celine Fernandez and Andreas Festa and Hugo Fitipaldi and Phillippe Froguel and Valborg Gudmundsdottir and Vilmundur Gudnason and Gerl, {Mathias J.} and {van der Heijden}, {Amber A.} and Jennings, {Lori L.} and Hansen, {Michael K.} and Min Kim and Isabelle Leclerc and Christian Klose and Dmitry Kuznetsov and {Mansour Aly}, Dina and Florence Mehl and Diana Marek and Olle Melander and Anne Niknejad and Filip Ottosson and Imre Pavo and Kevin Duffin and Syed, {Samreen K.} and Shaw, {Janice L.} and Over Cabrera and Pullen, {Timothy J.} and Kai Simons and Michele Solimena and Tommi Suvitaival and Asger Wretlind and Peter Rossing and Valeriya Lyssenko and {Legido Quigley}, Cristina and Leif Groop and Bernard Thorens and Franks, {Paul W.} and Lim, {Gareth E.} and Jennifer Estall and Mark Ibberson and Beulens, {Joline W. J.} and {{\textquoteright}t Hart}, {Leen M.} and Pearson, {Ewan R.} and Rutter, {Guy A.}",

note = "Funding Information: We acknowledge the support of the Health Informatics Centre, University of Dundee for managing and supplying the anonymised data. The authors wish to thank the Core-IT group of SIB Swiss Institute of Bioinformatics and in particular Jorge Molina for expert technical help in setting up and maintaining the federated database. G.A.R. thanks Claudio Elgueta Karstegl for technical support. The authors thank participants of the included cohorts. We are grateful to M{\'e}lanie Gu{\'e}vremont and the CRCHUM Cellular Physiology core facility for beta cell mass analyses. The ANDIS study was financed by Swedish governmental funding of clinical research (ALF), the Faculty of Medicine at Lund University, the Swedish Research Council project grant no. 2020-02191 and strategic research area grant no. 2009-1039 (EXODIAB), from the Swedish Foundation for Strategic Research IRC15-0067 (LUDC-IRC) and Vinnova Swelife. E.R.P. holds a Wellcome Trust New Investigator Award (102820/Z/13/Z). G.A.R. was supported by a Wellcome Trust Investigator Award (212625/Z/18/Z), MRC Programme grants (MR/R022259/1, MR/J0003042/1, MR/L020149/1), an Experimental Challenge Grant (DIVA, MR/L02036X/1), a Diabetes UK Project grant (BDA16/0005485) and Innovation Canada for a John R Evans Leader Award. G.E.L. was supported by a CIHR Project Grant (PJT-153144) and holds the Canada Research Chair in Adipocyte Development. This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking, under grant agreement no. 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI), under contract no. 16.0097. Va.G. is supported by the Icelandic Research Fund (grant no. 184845-051). The Hoorn DCS cohort was supported by grants from the Netherlands Organisation for Health Research and Development (113102006, 459001015). J.E. is supported by the CIHR (PJT-168853). Funding Information: We acknowledge the support of the Health Informatics Centre, University of Dundee for managing and supplying the anonymised data. The authors wish to thank the Core-IT group of SIB Swiss Institute of Bioinformatics and in particular Jorge Molina for expert technical help in setting up and maintaining the federated database. G.A.R. thanks Claudio Elgueta Karstegl for technical support. The authors thank participants of the included cohorts. We are grateful to M{\'e}lanie Gu{\'e}vremont and the CRCHUM Cellular Physiology core facility for beta cell mass analyses. The ANDIS study was financed by Swedish governmental funding of clinical research (ALF), the Faculty of Medicine at Lund University, the Swedish Research Council project grant no. 2020-02191 and strategic research area grant no. 2009-1039 (EXODIAB), from the Swedish Foundation for Strategic Research IRC15-0067 (LUDC-IRC) and Vinnova Swelife. E.R.P. holds a Wellcome Trust New Investigator Award (102820/Z/13/Z). G.A.R. was supported by a Wellcome Trust Investigator Award (212625/Z/18/Z), MRC Programme grants (MR/R022259/1, MR/J0003042/1, MR/L020149/1), an Experimental Challenge Grant (DIVA, MR/L02036X/1), a Diabetes UK Project grant (BDA16/0005485) and Innovation Canada for a John R Evans Leader Award. G.E.L. was supported by a CIHR Project Grant (PJT-153144) and holds the Canada Research Chair in Adipocyte Development. This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking, under grant agreement no. 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI), under contract no. 16.0097. Va.G. is supported by the Icelandic Research Fund (grant no. 184845-051). The Hoorn DCS cohort was supported by grants from the Netherlands Organisation for Health Research and Development (113102006, 459001015). J.E. is supported by the CIHR (PJT-168853). Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = dec,

day = "1",

doi = "https://doi.org/10.1038/s41467-023-38148-7",

language = "English",

volume = "14",

journal = "Nature communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

number = "1",

}

Slieker, RC, Donnelly, LA, Akalestou, E, Lopez-Noriega, L, Melhem, R, Güneş, A, Abou Azar, F, Efanov, A, Georgiadou, E, Muniangi-Muhitu, H, Sheikh, M, Giordano, GN, Åkerlund, M, Ahlqvist, E, Ali, A, Banasik, K, Brunak, SR, Barovic, M, Bouland, GA, Burdet, F, Canouil, M, Dragan, I, Elders, PJM, Fernandez, C, Festa, A, Fitipaldi, H, Froguel, P, Gudmundsdottir, V, Gudnason, V, Gerl, MJ, van der Heijden, AA, Jennings, LL, Hansen, MK, Kim, M, Leclerc, I, Klose, C, Kuznetsov, D, Mansour Aly, D, Mehl, F, Marek, D, Melander, O, Niknejad, A, Ottosson, F, Pavo, I, Duffin, K, Syed, SK, Shaw, JL, Cabrera, O, Pullen, TJ, Simons, K, Solimena, M, Suvitaival, T, Wretlind, A, Rossing, P, Lyssenko, V, Legido Quigley, C, Groop, L, Thorens, B, Franks, PW, Lim, GE, Estall, J, Ibberson, M, Beulens, JWJ, ’t Hart, LM, Pearson, ER & Rutter, GA 2023, 'Identification of biomarkers for glycaemic deterioration in type 2 diabetes', Nature communications, vol. 14, no. 1, 2533. https://doi.org/10.1038/s41467-023-38148-7

TY - JOUR

T1 - Identification of biomarkers for glycaemic deterioration in type 2 diabetes

AU - Slieker, Roderick C.

AU - Donnelly, Louise A.

AU - Akalestou, Elina

AU - Lopez-Noriega, Livia

AU - Melhem, Rana

AU - Güneş, Ayşim

AU - Abou Azar, Frederic

AU - Efanov, Alexander

AU - Georgiadou, Eleni

AU - Muniangi-Muhitu, Hermine

AU - Sheikh, Mahsa

AU - Giordano, Giuseppe N.

AU - Åkerlund, Mikael

AU - Ahlqvist, Emma

AU - Ali, Ashfaq

AU - Banasik, Karina

AU - Brunak, S. ren

AU - Barovic, Marko

AU - Bouland, Gerard A.

AU - Burdet, Frédéric

AU - Canouil, Mickaël

AU - Dragan, Iulian

AU - Elders, Petra J. M.

AU - Fernandez, Celine

AU - Festa, Andreas

AU - Fitipaldi, Hugo

AU - Froguel, Phillippe

AU - Gudmundsdottir, Valborg

AU - Gudnason, Vilmundur

AU - Gerl, Mathias J.

AU - van der Heijden, Amber A.

AU - Jennings, Lori L.

AU - Hansen, Michael K.

AU - Kim, Min

AU - Leclerc, Isabelle

AU - Klose, Christian

AU - Kuznetsov, Dmitry

AU - Mansour Aly, Dina

AU - Mehl, Florence

AU - Marek, Diana

AU - Melander, Olle

AU - Niknejad, Anne

AU - Ottosson, Filip

AU - Pavo, Imre

AU - Duffin, Kevin

AU - Syed, Samreen K.

AU - Shaw, Janice L.

AU - Cabrera, Over

AU - Pullen, Timothy J.

AU - Simons, Kai

AU - Solimena, Michele

AU - Suvitaival, Tommi

AU - Wretlind, Asger

AU - Rossing, Peter

AU - Lyssenko, Valeriya

AU - Legido Quigley, Cristina

AU - Groop, Leif

AU - Thorens, Bernard

AU - Franks, Paul W.

AU - Lim, Gareth E.

AU - Estall, Jennifer

AU - Ibberson, Mark

AU - Beulens, Joline W. J.

AU - ’t Hart, Leen M.

AU - Pearson, Ewan R.

AU - Rutter, Guy A.

N1 - Funding Information: We acknowledge the support of the Health Informatics Centre, University of Dundee for managing and supplying the anonymised data. The authors wish to thank the Core-IT group of SIB Swiss Institute of Bioinformatics and in particular Jorge Molina for expert technical help in setting up and maintaining the federated database. G.A.R. thanks Claudio Elgueta Karstegl for technical support. The authors thank participants of the included cohorts. We are grateful to Mélanie Guévremont and the CRCHUM Cellular Physiology core facility for beta cell mass analyses. The ANDIS study was financed by Swedish governmental funding of clinical research (ALF), the Faculty of Medicine at Lund University, the Swedish Research Council project grant no. 2020-02191 and strategic research area grant no. 2009-1039 (EXODIAB), from the Swedish Foundation for Strategic Research IRC15-0067 (LUDC-IRC) and Vinnova Swelife. E.R.P. holds a Wellcome Trust New Investigator Award (102820/Z/13/Z). G.A.R. was supported by a Wellcome Trust Investigator Award (212625/Z/18/Z), MRC Programme grants (MR/R022259/1, MR/J0003042/1, MR/L020149/1), an Experimental Challenge Grant (DIVA, MR/L02036X/1), a Diabetes UK Project grant (BDA16/0005485) and Innovation Canada for a John R Evans Leader Award. G.E.L. was supported by a CIHR Project Grant (PJT-153144) and holds the Canada Research Chair in Adipocyte Development. This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking, under grant agreement no. 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI), under contract no. 16.0097. Va.G. is supported by the Icelandic Research Fund (grant no. 184845-051). The Hoorn DCS cohort was supported by grants from the Netherlands Organisation for Health Research and Development (113102006, 459001015). J.E. is supported by the CIHR (PJT-168853). Funding Information: We acknowledge the support of the Health Informatics Centre, University of Dundee for managing and supplying the anonymised data. The authors wish to thank the Core-IT group of SIB Swiss Institute of Bioinformatics and in particular Jorge Molina for expert technical help in setting up and maintaining the federated database. G.A.R. thanks Claudio Elgueta Karstegl for technical support. The authors thank participants of the included cohorts. We are grateful to Mélanie Guévremont and the CRCHUM Cellular Physiology core facility for beta cell mass analyses. The ANDIS study was financed by Swedish governmental funding of clinical research (ALF), the Faculty of Medicine at Lund University, the Swedish Research Council project grant no. 2020-02191 and strategic research area grant no. 2009-1039 (EXODIAB), from the Swedish Foundation for Strategic Research IRC15-0067 (LUDC-IRC) and Vinnova Swelife. E.R.P. holds a Wellcome Trust New Investigator Award (102820/Z/13/Z). G.A.R. was supported by a Wellcome Trust Investigator Award (212625/Z/18/Z), MRC Programme grants (MR/R022259/1, MR/J0003042/1, MR/L020149/1), an Experimental Challenge Grant (DIVA, MR/L02036X/1), a Diabetes UK Project grant (BDA16/0005485) and Innovation Canada for a John R Evans Leader Award. G.E.L. was supported by a CIHR Project Grant (PJT-153144) and holds the Canada Research Chair in Adipocyte Development. This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking, under grant agreement no. 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI), under contract no. 16.0097. Va.G. is supported by the Icelandic Research Fund (grant no. 184845-051). The Hoorn DCS cohort was supported by grants from the Netherlands Organisation for Health Research and Development (113102006, 459001015). J.E. is supported by the CIHR (PJT-168853). Publisher Copyright: © 2023, The Author(s).

PY - 2023/12/1

Y1 - 2023/12/1

N2 - We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

AB - We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

UR - http://www.scopus.com/inward/record.url?scp=85158018722&partnerID=8YFLogxK

U2 - https://doi.org/10.1038/s41467-023-38148-7

DO - https://doi.org/10.1038/s41467-023-38148-7

M3 - Article

C2 - 37137910

SN - 2041-1723

VL - 14

JO - Nature communications

JF - Nature communications

IS - 1

M1 - 2533

ER -

Identification of biomarkers for glycaemic deterioration in type 2 diabetes

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