Proteomic analysis to identify candidate biomarkers associated with type 1 diabetes

Omics to Unveil Diabetes Mellitus Pathogenesis and Biomarkers: Focus on Proteomics, Lipidomics, and Metabolomics

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood sugar levels, resulting from either body's inability to produce or effectively utilize insulin. There are several types of DM, but the most common are type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM). DM is a complex disease and a global health concern, and the current clinical markers, such as fasting glucose, are helpful in the diagnosis of DM, but are not specific and sensitive, especially when measured on the beginning of the pathogenesis. Therefore, there is a pressing need to discover new early biomarkers that can provide an early diagnosis. Omics is an important field for the discovery of potential new biomarkers, especially proteomics, metabolomics, and lipidomics, where techniques such as liquid chromatography, mass spectrometry, and nuclear magnetic resonance are utilized to identify novel DM biomarkers and their pathways. In this review, we report papers that applied omics in the context of DM to identify new markers and their relationship with this disease, with the aim of elucidating new diagnostic techniques for the main types of DM.

Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes distinguishes markers of disease and C-peptide trajectory

AIMS/HYPOTHESIS

There is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs).

METHODS

Selected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years (n=86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs (n=194).

RESULTS

Eleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family.

CONCLUSIONS/INTERPRETATION

The association of several targeted proteins with fasting C-peptide/glucose levels in the first year after diagnosis suggests their connection with the underlying changes accompanying alterations in beta cell function in type 1 diabetes. Moreover, the direction of change in GPX3 during the first year was indicative of subsequent fasting C-peptide/glucose levels, and supports further investigation of this and other serum protein measurements in future studies of beta cell function in type 1 diabetes.

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

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.

Proteomics of high-density lipoprotein subfractions and subclinical atherosclerosis in type 1 diabetes mellitus: a case-control study

BACKGROUND

Subclinical atherosclerosis is frequently observed in type 1 diabetes (T1D) although the mechanisms and markers involved in the evolution to established cardiovascular disease are not well known. High-density lipoprotein cholesterol in T1D is normal or even high, and changes in its functionality and proteomics are considered. Our aim was to evaluate the proteomics of HDL subfractions in T1D and control subjects and its association with clinical variables, subclinical atherosclerosis markers and HDL functionality.

METHODS

A total of 50 individuals with T1D and 30 matched controls were included. Carotid-femoral pulse wave velocity (PWV), flow-mediated vasodilation (FMD), cardiovascular autonomic neuropathy (CAN), and ten-year cardiovascular risk (ASCVDR) were determined. Proteomics (parallel reaction monitoring) was determined in isolated HDL₂ and HDL₃ that were also utilized to measure cholesterol efflux from macrophages.

RESULTS

Among 45 quantified proteins, 13 in HDL₂ and 33 in HDL₃ were differentially expressed in T1D and control subjects. Six proteins related to lipid metabolism, one to inflammatory acute phase, one to complement system and one to antioxidant response were more abundant in HDL₂, while 14 lipid metabolism, three acute-phase, three antioxidants and one transport in HDL₃ of T1D subjects. Three proteins (lipid metabolism, transport, and unknown function) were more abundant in HDL₂; and ten (lipid metabolism, transport, protease inhibition), more abundant in HDL₃ of controls. Individuals with T1D had higher PWV and ten-year ASCVDR, and lower FMD, Cholesterol efflux from macrophages was similar between T1D and controls. Proteins in HDL₂ and HDL₃, especially related to lipid metabolism, correlated with PWV, CAN, cholesterol efflux, HDLc, hypertension, glycemic control, ten-year ASCVDR, and statins use.

CONCLUSION

HDL proteomics can be predictive of subclinical atherosclerosis in type 1 diabetes. Proteins that are not involved in reverse cholesterol transport may be associated with the protective role of HDL.

The Proteome of Circulating Large Extracellular Vesicles in Diabetes and Hypertension

Hypertension and diabetes induce vascular injury through processes that are not fully understood. Changes in extracellular vesicle (EV) composition could provide novel insights. Here, we examined the protein composition of circulating EVs from hypertensive, diabetic and healthy mice. EVs were isolated from transgenic mice overexpressing human renin in the liver (TtRhRen, hypertensive), OVE26 type 1 diabetic mice and wild-type (WT) mice. Protein content was analyzed using liquid chromatography-mass spectrometry. We identified 544 independent proteins, of which 408 were found in all groups, 34 were exclusive to WT, 16 were exclusive to OVE26 and 5 were exclusive to TTRhRen mice. Amongst the differentially expressed proteins, haptoglobin (HPT) was upregulated and ankyrin-1 (ANK1) was downregulated in OVE26 and TtRhRen mice compared with WT controls. Conversely, TSP4 and Co3A1 were upregulated and SAA4 was downregulated exclusively in diabetic mice; and PPN was upregulated and SPTB1 and SPTA1 were downregulated in hypertensive mice, compared to WT mice. Ingenuity pathway analysis identified enrichment in proteins associated with SNARE signaling, the complement system and NAD homeostasis in EVs from diabetic mice. Conversely, in EVs from hypertensive mice, there was enrichment in semaphroin and Rho signaling. Further analysis of these changes may improve understanding of vascular injury in hypertension and diabetes.

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

Aims

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 (DOI 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 251 unique proteins, with 27 (11%) 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 a subset of 3 proteins (C3, KNG1 & CFAH), 6 proteins (C3, C4A, APOA4, C4B, A2AP & BTD) and 7 proteins (C3, CLUS, APOA4, C6, A2AP, C1R & CFAI) have consistent regulation between multiple studies in samples from individuals at pre-seroconversion, 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.

UPLC-HDMSE to discover serum biomarkers in adults with type 1 diabetes

Type 1 diabetes (T1D) is a complex disease with metabolic and functional changes that can alter an individual's proteome. An LC-MS/MS analytical method, in an HDMS^E system, was used to identify differentially expressed proteins in the high abundance protein-depleted serum of T1D patients and healthy controls. Samples were processed in Progenesis QI for Proteomics software. A functional enrichment of the proteins was performed with Gene Ontology and ToppGene, and the interactions were visualized by STRING 11.5. As a result, 139 proteins were identified, 14 of which were downregulated in the serum of patients with T1D compared to controls. Most of the differentially expressed proteins were shown to be involved with the immune system, inflammation, and growth hormone stimulus response, and were associated with the progression of T1D. Differential protein expression data showed for the first-time changes in CPN2 expression levels in the serum of patients with T1D. Our findings indicate that these proteins are targets of interest for future investigations and for validation of protein biomarkers in T1D.

Maternal serum proteomic profiles of pregnant women with type 1 diabetes

Despite improvement in the care of diabetes over the years, pregnancy complicated by type 1 diabetes (T1DM) is still associated with adverse maternal and neonatal outcomes. To date, proteomics studies have been conducted to identify T1DM biomarkers in non-pregnant women, however, no studies included T1DM pregnant women. In this study serum proteomic profiling was conducted in pregnant women with T1DM in the late third trimester. Serum samples were collected from 40 women with T1DM and 38 healthy controls within 3 days before delivery at term pregnancy. Significant differences between serum proteomic patterns were revealed, showing discriminative peaks for complement C3 and C4-A, kininogen-1, and fibrinogen alpha chain. Quantification of selected discriminative proteins by ELISA kits was also performed. The serum concentration of kininogen-1 was significantly lower in women with T1DM than in controls. There were no significant differences in serum concentrations of complement C3 and complement C4-A between study groups. These data indicate that pregnant women with T1DM have a distinct proteomic profile involving proteins in the coagulation and inflammatory pathways. However, their utility as biomarkers of pregnancy complications in women with T1DM warrants further investigation.

Comprehensive profiling and kinetic studies of glycated lysine residues in human serum albumin

Lysine residues of proteins slowly react with glucose forming Amadori products. In hyperglycemic conditions, such as diabetes mellitus, this non-enzymatic glycation becomes more pervasive causing severe medical complications. The structure and conformation of a protein predisposes lysine sites to differing reactivity influenced by their steric availability and amino acid microenvironment. The goal of our study was to identify these sites in albumin and measure glycation affinities of lysine residues. We applied a bottom-up approach utilizing a combination of three LC-MS instruments: timsTOF, Orbitrap, and QTRAP. To prove applicability to samples of varying glycemic status, we compared in vitro glycated and non-glycated HSA, as well as diabetic and non-diabetic individual samples. The analysis of lysine glycation affinities based on peptide intensities provide a semi-quantitative approach, as the results depend on the mass spectrometry platform used. We found that glycation levels based on multiple reaction monitoring (MRM) quantitation better reflect individual glycemic status and that the glycation percentage for each site is in linear relation to all other sites. To develop an approach which more accurately reflects glycation affinity, we developed a kinetics model which uses results from stable isotope dilution HPLC-MRM methodology. Through glycation of albumin at different glucose concentrations, we determine the rate constants of glycation for every lysine residue by simultaneous comparative analysis.

Clinically Relevant Circulating Protein Biomarkers for Type 1 Diabetes: Evidence From a Two-Sample Mendelian Randomization Study

OBJECTIVE

To identify circulating proteins influencing type 1 diabetes susceptibility using Mendelian randomization (MR).

RESEARCH DESIGN AND METHODS

We used a large-scale two-sample MR study, using cis genetic determinants (protein quantitative trait loci [pQTL]) of up to 1,611 circulating proteins from five large genome-wide association studies, to screen for causal associations of these proteins with type 1 diabetes risk in 9,684 case subjects with type 1 diabetes and 15,743 control subjects. Further, pleiotropy-robust MR methods were used in sensitivity analyses using both cis and trans-pQTL.

RESULTS

We found that a genetically predicted SD increase in signal regulatory protein gamma (SIRPG) level was associated with increased risk of type 1 diabetes risk (MR odds ratio [OR] 1.66 [95% 1.36-2.03]; P = 7.1 × 10-7). The risk of type 1 diabetes increased almost twofold per genetically predicted standard deviation (SD) increase in interleukin-27 Epstein-Barr virus-induced 3 (IL27-EBI3) protein levels (MR OR 1.97 [95% CI 1.48-2.62]; P = 3.7 × 10-6). However, an SD increase in chymotrypsinogen B1 (CTRB1) was associated with decreased risk of type 1 diabetes (MR OR 0.84 [95% CI 0.77-0.90]; P = 6.1 × 10-6). Sensitivity analyses using MR methods testing for pleiotropy while including trans-pQTL showed similar results. While the MR-Egger suggested no pleotropic effect (P value MR-Egger intercept = 0.31), there was evidence of pleiotropy in MR-PRESSO (P value global test = 0.006).

CONCLUSIONS

We identified three novel circulating protein biomarkers associated with type 1 diabetes risk using an MR approach. These biomarkers are promising targets for development of drugs and/or of screening tools for early prediction of type 1 diabetes.

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

BACKGROUND

Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics.

METHODS

Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls.

RESULTS

The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects.

CONCLUSIONS

Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

MALDI-TOF Protein Profiling Reflects Changes in Type 1 Diabetes Patients Depending on the Increased Amount of Adipose Tissue, Poor Control of Diabetes and the Presence of Chronic Complications

Introduction: Protein profiling allows the determination of the presence of proteins marking various stages of the disease, and differentiates between people at risk of various diseases. In type 1 diabetes, protein profiling had been previously used to find blood markers other than islet autoantibodies to indicate the pancreatic beta cell destruction process and to reflect the progression of type 1 diabetes mellitus (T1DM). However, T1DM is an auto-immune disease and its clinical presentation changes in time of its duration. The aim of the study: To find differences in protein profiles in patients with type 1 diabetes according to diabetes control (HbA1c > 7%) and with presence of diabetic complications or obesity. It may help to identify subgroups of patients who may need a better clinical supervision and individualized treatment. Material and methods: A group of 103 patients with auto-immunologically confirmed T1DM, and meeting the following inclusion criteria: Caucasian race, duration of diabetes >5 years, were used in the study. Criteria of exclusion: past or present cancer (treated with chemo-/radiotherapy), diseases of the liver (ALT > 3 × ULN) except for people with simple hepatic steatosis, chronic renal disease (eGFR < 30 mL/1.73 m²/min), and acute inflammation (CRP > 5 mg/dL). The study group was divided in terms of the presence of chronic complications, obesity, or poor metabolic control (HbA1c > 7%). Protein profiling was completed by using the MALDI-TOF MS (matrix-assisted laser desorption/ionization-time of flight mass spectrometry) analyzer. Results: Differentiating proteins were identified in all of the groups. The groups burdened with complications, obesity, and poor metabolic control were characterized by increased levels of fibrinogen, complement C4 and C3. Conclusion: The groups of type 1 diabetes patients burdened with complications, obesity, and poor metabolic control were characterized by increased levels of fibrinogen, complement C4 and C3. Further detailed studies are necessary to determine more subtle changes in the proteomic profile of patients with type 1 diabetes.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Gingival crevicular fluid biomarkers in type 1 diabetes mellitus: A case-control study

OBJECTIVE

The aim of the study is to compare the levels of Gingival Crevicular Fluid (GCF) interleukin 8 (IL-8), matrix metalloproteinase 8 (MMP-8) and advanced glycated-end products (AGEs) in a cohort of type 1 diabetic (T1D) subjects and healthy controls.

MATERIAL AND METHODS

GCF samples and periodontal examination were assessed in 50 subjects with T1D (30 males and 20 females; mean age: 35.2 years) recruited from the Diabetology Unit of the Geneva University Hospitals and in 50 control subjects matched for gender, age and smoking status. Samples were assessed for IL-8 and MMP-8 using a bead array multianalyte detection system and for AGEs the ELISA. The two groups were compared using the Wilcoxon signed rank test.

RESULTS

The mean HbA1c differed significantly between the groups (8.3% for the T1D group vs. 5.2% for the control group, p < 0.001). T1D subjects had significantly more plaque and gingival inflammation and presented more sites with bleeding on probing compared to the controls. The GCF levels of IL-8, MMP-8 and AGEs did not differ significantly between the groups. Further analysis of the GCF markers in younger (<40 years) and older (≥40 years) cohorts, revealed no significant differences between younger diabetics and controls or between older diabetics and controls. When the groups were divided according to their glycemic status (HbA1c 6.1-8, and > 8%), again no significant differences could be identified for any of the biochemical markers.

CONCLUSIONS

T1D subjects, particularly the younger ones, exhibited more inflammation compared to the matched healthy controls. Results on the GCF expression of IL-8, MMP-8 and AGEs did not differ between the groups. The diabetic population of our cohort was for the most part fairly-controlled, with little if any complications and with presence of only mild type of periodontal disease, as 68% had gingivitis.

The Role of Inflammation in Diabetic Retinopathy

Inflammation is central to pathogenic processes in diabetes mellitus and the metabolic syndrome and particularly implicates innate immunity in the development of complications. Inflammation is a primary event in Type 1 diabetes where infectious (viral) and/or autoimmune processes initiate disease; in contrast, chronic inflammation is typical in Type 2 diabetes and is considered a sequel to increasing insulin resistance and disturbed glucose metabolism. Diabetic retinopathy (DR) is perceived as a vascular and neurodegenerative disease which occurs after some years of poorly controlled diabetes. However, many of the clinical features of DR are late events and reflect the nature of the retinal architecture and its cellular composition. Retinal microvascular disease is, in fact, an early event pathogenetically, induced by low grade, persistent leukocyte activation which causes repeated episodes of capillary occlusion and, progressive, attritional retinal ischemia. The later, overt clinical signs of DR are a consequence of the retinal ischemia. Metabolic dysregulation involving both lipid and glucose metabolism may lead to leukocyte activation. On a molecular level, we have shown that macrophage-restricted protein tyrosine phosphatase 1B (PTP1B) is a key regulator of inflammation in the metabolic syndrome involving insulin resistance and it is possible that PTP1B dysregulation may underlie retinal microvascular disease. We have also shown that adherent CCR5⁺CD11b⁺ monocyte macrophages appear to be selectively involved in retinal microvascular occlusion. In this review, we discuss the relationship between early leukocyte activation and the later features of DR, common pathogenetic processes between diabetic microvascular disease and other vascular retinopathies, the mechanisms whereby leukocyte activation is induced in hyperglycemia and dyslipidemia, the signaling mechanisms involved in diabetic microvascular disease, and possible interventions which may prevent these retinopathies. We also address a possible role for adaptive immunity in DR. Although significant improvements in treatment of DR have been made with intravitreal anti-VEGF therapy, a sizeable proportion of patients, particularly with sight-threatening macular edema, fail to respond. Alternative therapies targeting inflammatory processes may offer an advantage.

Alzheimer's disease and type 2 diabetes mellitus: A systematic review of proteomic studies

Similar to dementia, the risk for developing type 2 diabetes mellitus (T2DM) increases with age, and T2DM also increases the risk for dementia, particularly Alzheimer's disease (AD). Although T2DM is primarily a peripheral disorder and AD is a central nervous system disease, both share some common features as they are chronic and complex diseases, and both show involvement of oxidative stress and inflammation in their progression. These characteristics suggest that T2DM may be associated with AD, which gave rise to a new term, type 3 diabetes (T3DM). In this study, we searched for matching peripheral proteomic biomarkers of AD and T2DM based in a systematic review of the available literature. We identified 17 common biomarkers that were differentially expressed in both patients with AD or T2DM when compared with healthy controls. These biomarkers could provide a useful workflow for screening T2DM patients at risk to develop AD.

Urinary Peptides Associated Closely with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common disease of pregnant women, which has a higher incidence in recent years. The purpose of this study is to explore urinary biomarkers that could predict and monitor gestational diabetes mellitus (GDM). Urine samples from 30 normal pregnant women and 78 GDM patients were collected and purified by weak cationic exchange magnetic beads (MB-WCX), then analyzed by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS). The urinary peptide signatures of the two groups were compared by BioExplorer software. The potential ability of the differently expressed peptides to distinguish GDM patients from normal pregnant women was evaluated by receiver operating characteristic (ROC) analysis. At last, the differently expressed peptides were identified by liquid chromatography tandem mass spectrometry (LC-MS). There were four differently expressed peptides (m/z 1000.5, 1117.5, 1142.9, and 2022.9) between two groups, which were identified as fragments of urinary albumin, α2-macroglobulin, human hemopexin, and α1-microglobulin, respectively. The diagnostic efficacy of m/z 1142.9 was better than the other peptides. The area under the curve (AUC) of the m/z 1142.9 was 0.690 (95% CI: 0.583-0.796). The discovery of urinary polypeptides provides the possibility for the early prediction of GDM and the monitoring of glucose metabolism in GDM patients by a noninvasive method.

Effects of Different Dietary Vegetable Lipid Sources on Health Status in Nile Tilapia (Oreochromis niloticus): Haematological Indices, Immune Response Parameters and Plasma Proteome

This study aimed to investigate the effects of DLs, including palm oil (PO; an SFAs), linseed oil (LO; n-3 PUFAs) and soybean oil (SBO; n-6 PUFAs) on the health status of Nile tilapia (Oreochromis niloticus) during adulthood. Three experimental diets incorporating PO, LO or SBO were fed to adult Nile tilapia for a period of 90 days, and haematological and innate immune parameters were evaluated. Proteome analysis was also conducted to evaluate the effects of DLs on plasma proteins. The tested DLs had no significant effects on red blood cell (RBC) count, haematocrit, haemoglobin, and total immunoglobulin and lysozyme activity. Dietary LO led to increased alternative complement 50 activity (ACH50), and proteome analysis revealed that PO and SBO enhanced A2ML, suggesting that different DLs promote immune system via different processes. Dietary LO or SBO increased the expression of several proteins involved in coagulation activity such as KNG1, HRG and FGG. Increased HPX in fish fed with PO suggests that SFAs are utilised in heme lipid-oxidation. Overall, DLs with distinct fatty acids (FAs) affect several parameters corresponding to health status in Nile tilapia, and dietary LO and SBO seemed to strengthen health in this species.

Identification and validation of common molecular targets of hydroxytyrosol

Hydroxytyrosol (HT) is involved in healthful activities and is beneficial to lipid metabolism. Many investigations focused on finding tissue-specific targets of HT through the use of different omics approaches such as transcriptomics and proteomics. However, it is not clear which (if any) of the potential molecular targets of HT reported in different studies are concurrently affected in various tissues. Following the bioinformatic analyses of publicly available data from a selection of in vivo studies involving HT-supplementation, we selected differentially expressed lipid metabolism-related genes and proteins common to more than one study, for validation in rodent liver samples from the entire selection. Four miRNAs (miR-802-5p, miR-423-3p, miR-30a-5p, and miR-146b-5p) responded to HT supplementation. Of note, miR-802-5p was commonly regulated in the liver and intestine. Our premise was that, in an organ crucial for lipid metabolism such as the liver, consistent modulation should be found for a specific target of HT even if different doses and duration of HT supplementation were used in vivo. Even though our results show inconsistency regarding differentially expressed lipid metabolism-related genes and proteins across studies, we found Fgf21 and Rora as potential novel targets of HT. Omics approaches should be fine-tuned to better exploit the available databases.