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Review
. 2023 Sep 21;20(1):38.
doi: 10.1186/s12014-023-09429-6.

Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response

Soumyadeep Sarkar  1 , Emily C Elliott  1 , Hayden R Henry  1 , Ivo Díaz Ludovico  1 , John T Melchior  1   2 , Ashley Frazer-Abel  3 , Bobbie-Jo Webb-Robertson  1 , W Sean Davidson  2 , V Michael Holers  3 , Marian J Rewers  4 , Thomas O Metz  1 , Ernesto S Nakayasu  5
Affiliations
Review

Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response

Soumyadeep Sarkar et al. Clin Proteomics. .

Abstract

Background: Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development.

Methods: This systematic review was registered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/N8TSA ). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria.

Results: A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development.

Conclusions: Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.

Keywords: Biomarker; Plasma; Proteomics; Type 1 diabetes.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
PRISMA flow chart of literature search strategy, screening, and exclusion criteria
Fig. 2
Fig. 2
Pathway analysis of the protein biomarkers. This network represents proteins linked to their respective consolidated pathways from KEGG. Pathways were consolidated based on their overlap and redundancy. The nodes are colored based on the number of studies that the proteins were shown to be significantly regulated
Fig. 3
Fig. 3
Complement cascade. The diagram represents all the complement pathway proteins denoted by orange color identified in our systematic review. The Image was modified from “Complement cascade pathway” on the Reactome website (https://reactome.org/PathwayBrowser/#/R-HSA-166658 with StableID: R-HSA-166658)
Fig. 4
Fig. 4
Immune pathways. The diagram represents proteins identified in the systematic review belonging to immune pathways and functions: extracellular matrix, cytoskeleton/actin filament, oxidative stress, gene expression, inflammatory signaling, antigen presentation, cytokine/chemokine, opsonization, antibodies, and other immune receptors/regulators. Proteins were annotated into different pathways with DAVID and by their function description in UniProt. Proteins are listed using their UniProt gene names
Fig. 5
Fig. 5
Overlap of T1D-relevant proteins with high- (HDL)/ low- (LDL) density lipoproteome. A Venn diagram showing common protein hits (grey) between the HDL/LDL proteome [52] (black) and those reported in our systematic review (white). B Venn diagram detailing the T1D stage as pre-seroconversion (pre-sero), post-seroconversion (post-sero) and post-diagnosis of the 119 HDL/LDL/T1D shared proteins from A. C Gene Ontology of HDL lipoprotein-known functions of pre-seroconversion reported proteins. D Heatmap of apolipoproteins with altered levels reported in at least one stage of T1D development. Up (Red color) are upregulated proteins and down (Green color) are downregulated proteins. Proteins are named using their UniProt gene names. Panel C was modified from a published figure by Davidson et al. (copyright permission was obtained from the publisher, license number: 5433910818199) [52]
Fig. 6
Fig. 6
Potential biomarkers list. It is a heatmap of all the protein biomarkers identified by multiple proteomic papers (3 or more times). Proteins that the studies have not reported are represented as blank. “T” denotes the targeted proteomic approach, whereas “U” denotes the untargeted proteomics. Proteins are listed based on their gene names. Down—significantly downregulated proteins, sero. seroconversion, Up—significantly upregulated proteins
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