Harnessing the power of proteomics in precision diabetes medicine

被引:7
作者
Kurgan, Nigel [1 ]
Larsen, Jeppe Kjaergaard [1 ]
Deshmukh, Atul S. [1 ]
机构
[1] Univ Copenhagen, Novo Nord Fdn Ctr Basic Metab Res, Copenhagen, Denmark
关键词
Affinity proteomics; Diabetes; LC-MS/MS; Precision medicine; Proteogenomics; Proteomics; Review; PERSONALIZED MEDICINE; PLASMA PROTEOME; TYPE-2; SUBGROUPS; PROTEINS; GENETICS; INSULIN; RISK; METABOLOMICS; HEALTH;
D O I
10.1007/s00125-024-06097-5
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.
引用
收藏
页码:783 / 797
页数:15
相关论文
共 147 条
[1]   Molecular quantitative trait loci [J].
Aguet, Francois ;
Alasoo, Kaur ;
Li, Yang, I ;
Battle, Alexis ;
Im, Hae Kyung ;
Montgomery, Stephen B. ;
Lappalainen, Tuuli .
NATURE REVIEWS METHODS PRIMERS, 2023, 3 (01)
[2]   Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables [J].
Ahlqvist, Emma ;
Storm, Petter ;
Karajamaki, Annemari ;
Martinell, Mats ;
Dorkhan, Mozhgan ;
Carlsson, Annelie ;
Vikman, Petter ;
Prasad, Rashmi B. ;
Aly, Dina Mansour ;
Almgren, Peter ;
Wessman, Ylva ;
Shaat, Nael ;
Spegel, Peter ;
Mulder, Hindrik ;
Lindholm, Eero ;
Melander, Olle ;
Hansson, Ola ;
Malmqvist, Ulf ;
Lernmark, Ake ;
Lahti, Kaj ;
Forsen, Tom ;
Tuomi, Tiinamaija ;
Rosengren, Anders H. ;
Groop, Leif .
LANCET DIABETES & ENDOCRINOLOGY, 2018, 6 (05) :361-369
[3]  
Ahmad Jamal, 2012, Foot (Edinb), V22, P194, DOI 10.1016/j.foot.2012.03.015
[4]   Plasma Proteome Profiling Reveals Dynamics of Inflammatory and Lipid Homeostasis Markers after Roux-En-Y Gastric Bypass Surgery [J].
Albrechtsen, Nicolai J. Wewer ;
Geyer, Philipp E. ;
Doll, Sophia ;
Treit, Peter V. ;
Bojsen-Moller, Kirstine N. ;
Martinussen, Christoffer ;
Jorgensen, Nils B. ;
Torekov, Signe S. ;
Meier, Florian ;
Niu, Lili ;
Santos, Alberto ;
Keilhauer, Eva C. ;
Holst, Jens J. ;
Madsbad, Sten ;
Mann, Matthias .
CELL SYSTEMS, 2018, 7 (06) :601-+
[5]   Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models [J].
Allesoe, Rosa Lundbye ;
Lundgaard, Agnete Troen ;
Medina, Ricardo Hernandez ;
Aguayo-Orozco, Alejandro ;
Johansen, Joachim ;
Nissen, Jakob Nybo ;
Brorsson, Caroline ;
Mazzoni, Gianluca ;
Niu, Lili ;
Biel, Jorge Hernansanz ;
Brasas, Valentas ;
Webel, Henry ;
Benros, Michael Eriksen ;
Pedersen, Anders Gorm ;
Chmura, Piotr Jaroslaw ;
Jacobsen, Ulrik Plesner ;
Mari, Andrea ;
Koivula, Robert ;
Mahajan, Anubha ;
Vinuela, Ana ;
Tajes, Juan Fernandez ;
Sharma, Sapna ;
Haid, Mark ;
Hong, Mun-Gwan ;
Musholt, Petra B. ;
De Masi, Federico ;
Vogt, Josef ;
Pedersen, Helle Krogh ;
Gudmundsdottir, Valborg ;
Jones, Angus ;
Kennedy, Gwen ;
Bell, Jimmy ;
Thomas, E. Louise ;
Frost, Gary ;
Thomsen, Henrik ;
Hansen, Elizaveta ;
Hansen, Tue Haldor ;
Vestergaard, Henrik ;
Muilwijk, Mirthe ;
Blom, Marieke T. ;
Hart, Leen M. T. ;
Pattou, Francois ;
Raverdy, Violeta ;
Brage, Soren ;
Kokkola, Tarja ;
Heggie, Alison ;
McEvoy, Donna ;
Mourby, Miranda ;
Kaye, Jane ;
Hattersley, Andrew .
NATURE BIOTECHNOLOGY, 2023, 41 (03) :399-+
[6]   The human plasma proteome - History, character, and diagnostic prospects [J].
Anderson, NL ;
Anderson, NG .
MOLECULAR & CELLULAR PROTEOMICS, 2002, 1 (11) :845-867
[7]   Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study [J].
Anjana, Ranjit Mohan ;
Baskar, Viswanathan ;
Nair, Anand Thakarakkattil Narayanan ;
Jebarani, Saravanan ;
Siddiqui, Moneeza Kalhan ;
Pradeepa, Rajendra ;
Unnikrishnan, Ranjit ;
Palmer, Colin ;
Pearson, Ewan ;
Mohan, Viswanathan .
BMJ OPEN DIABETES RESEARCH & CARE, 2020, 8 (01)
[8]   A guide to multi-omics data collection and integration for translational medicine [J].
Athieniti, Efi ;
Spyrou, George M. .
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2023, 21 :134-149
[9]   A Novel LC System Embeds Analytes in Pre-formed Gradients for Rapid, Ultra-robust Proteomics [J].
Bache, Nicolai ;
Geyer, Philipp E. ;
Bekker-Jensen, Dorte B. ;
Hoerning, Ole ;
Falkenby, Lasse ;
Treit, Peter V. ;
Doll, Sophia ;
Paron, Igor ;
Mueller, Johannes B. ;
Meier, Florian ;
Olsen, Jesper V. ;
Vorm, Ole ;
Mann, Matthias .
MOLECULAR & CELLULAR PROTEOMICS, 2018, 17 (11) :2284-2296
[10]   MS-Based Proteomics of Body Fluids: The End of the Beginning [J].
Bader, Jakob M. ;
Albrecht, Vincent ;
Mann, Matthias .
MOLECULAR & CELLULAR PROTEOMICS, 2023, 22 (07)