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
[51]   The landscape of expression and alternative splicing variation across human traits [J].
Garcia-Perez, Raquel ;
Ramirez, Jose Miguel ;
Ripoll-Cladellas, Aida ;
Chazarra-Gil, Ruben ;
Oliveros, Winona ;
Soldatkina, Oleksandra ;
Bosio, Mattia ;
Rognon, Paul Joris ;
Capella-Gutierrez, Salvador ;
Calvo, Miquel ;
Reverter, Ferran ;
Guigo, Roderic ;
Aguet, Francois ;
Ferreira, Pedro G. ;
Ardlie, Kristin G. ;
Mele, Marta .
CELL GENOMICS, 2023, 3 (01)
[52]   Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies [J].
Geyer, Philipp E. ;
Voytik, Eugenia ;
Treit, Peter V. ;
Doll, Sophia ;
Kleinhempel, Alisa ;
Niu, Lili ;
Mueller, Johannes B. ;
Buchholtz, Marie-Luise ;
Bader, Jakob M. ;
Teupser, Daniel ;
Holdt, Lesca M. ;
Mann, Matthias .
EMBO MOLECULAR MEDICINE, 2019, 11 (11)
[53]   Proteomics reveals the effects of sustained weight loss on the human plasma proteome [J].
Geyer, Philipp E. ;
Albrechtsen, Nicolai J. Wewer ;
Tyanova, Stefka ;
Grassl, Niklas ;
Iepsen, Eva W. ;
Lundgren, Julie ;
Madsbad, Sten ;
Holst, Jens J. ;
Torekov, Signe S. ;
Mann, Matthias .
MOLECULAR SYSTEMS BIOLOGY, 2016, 12 (12)
[54]   Plasma Proteome Profiling to Assess Human Health and Disease [J].
Geyer, Philipp E. ;
Kulak, Nils A. ;
Pichler, Garwin ;
Holdt, Lesca M. ;
Teupser, Daniel ;
Mann, Matthias .
CELL SYSTEMS, 2016, 2 (03) :185-195
[55]   Connecting Genomics and Proteomics to Identify Protein Biomarkers for Adult and Youth-Onset Type 2 Diabetes: A Two-Sample Mendelian Randomization Study [J].
Ghanbari, Faegheh ;
Yazdanpanah, Nahid ;
Yazdanpanah, Mojgan ;
Richards, J. Brent ;
Manousaki, Despoina .
DIABETES, 2022, 71 (06) :1324-1337
[56]   Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation [J].
Giuliani, Alessandro ;
Bui, Thuy Tien ;
Helmy, Mohamed ;
Selvarajoo, Kumar .
GENOMICS, 2022, 114 (01) :215-228
[57]   Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery [J].
Gold, Larry ;
Ayers, Deborah ;
Bertino, Jennifer ;
Bock, Christopher ;
Bock, Ashley ;
Brody, Edward N. ;
Carter, Jeff ;
Dalby, Andrew B. ;
Eaton, Bruce E. ;
Fitzwater, Tim ;
Flather, Dylan ;
Forbes, Ashley ;
Foreman, Trudi ;
Fowler, Cate ;
Gawande, Bharat ;
Goss, Meredith ;
Gunn, Magda ;
Gupta, Shashi ;
Halladay, Dennis ;
Heil, Jim ;
Heilig, Joe ;
Hicke, Brian ;
Husar, Gregory ;
Janjic, Nebojsa ;
Jarvis, Thale ;
Jennings, Susan ;
Katilius, Evaldas ;
Keeney, Tracy R. ;
Kim, Nancy ;
Koch, Tad H. ;
Kraemer, Stephan ;
Kroiss, Luke ;
Le, Ngan ;
Levine, Daniel ;
Lindsey, Wes ;
Lollo, Bridget ;
Mayfield, Wes ;
Mehan, Mike ;
Mehler, Robert ;
Nelson, Sally K. ;
Nelson, Michele ;
Nieuwlandt, Dan ;
Nikrad, Malti ;
Ochsner, Urs ;
Ostroff, Rachel M. ;
Otis, Matt ;
Parker, Thomas ;
Pietrasiewicz, Steve ;
Resnicow, Daniel I. ;
Rohloff, John .
PLOS ONE, 2010, 5 (12)
[58]   Identifying Low-Abundance Biomarkers Aptamer-Based Proteomics Potentially Enables More Sensitive Detection in Cardiovascular Diseases [J].
Gramolini, Anthony ;
Lau, Edward ;
Liu, Peter P. .
CIRCULATION, 2016, 134 (04) :286-289
[59]   A genome-wide association study of serum proteins reveals shared loci with common diseases [J].
Gudjonsson, Alexander ;
Gudmundsdottir, Valborg ;
Axelsson, Gisli T. ;
Gudmundsson, Elias F. ;
Jonsson, Brynjolfur G. ;
Launer, Lenore J. ;
Lamb, John R. ;
Jennings, Lori L. ;
Aspelund, Thor ;
Emilsson, Valur ;
Gudnason, Vilmundur .
NATURE COMMUNICATIONS, 2022, 13 (01)
[60]   Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes [J].
Gudmundsdottir, Valborg ;
Zaghlool, Shaza B. ;
Emilsson, Valur ;
Aspelund, Thor ;
Ilkov, Marjan ;
Gudmundsson, Elias F. ;
Jonsson, Stefan M. ;
Zilhao, Nuno R. ;
Lamb, John R. ;
Suhre, Karsten ;
Jennings, Lori L. ;
Gudnason, Vilmundur .
DIABETES, 2020, 69 (08) :1843-1853