Serological Proteome Analysis (SERPA) as a tool for the identification of new candidate autoantigens in type 1 diabetes

Breaking tolerance: autoantibodies can target protein posttranslational modifications

Autoantibodies (AAb) are an immunological resource ripe for exploitation in cancer detection and treatment. Key to this translation is a better understanding of the self-epitope that AAb target in tumor tissue, but do not bind to in normal tissue. Posttranslational modifications (PTMs) on self-proteins are known to break tolerance in many autoimmune diseases and have also recently been described in cancer. This scope of possible autoantigens is quite broad and new high-dimensional and -throughput technologies to probe this repertoire will be necessary to fully exploit their potential. Here, we discuss the strengths and weaknesses of existing high-throughput platforms to detect AAb, review the current methods for characterizing immunogenic PTMs, describe the main challenges to identifying disease-relevant antigens and suggest the properties of future technologies that may be able to address these challenges. We conclude that exploiting the evolutionary power of the immune system to distinguish between self and nonself has great potential to be translated into antibody-based clinical applications.

An Autoantigen Atlas From Human Lung HFL1 Cells Offers Clues to Neurological and Diverse Autoimmune Manifestations of COVID-19

COVID-19 is accompanied by a myriad of both transient and long-lasting autoimmune responses. Dermatan sulfate (DS), a glycosaminoglycan crucial for wound healing, has unique affinity for autoantigens (autoAgs) from apoptotic cells. DS-autoAg complexes are capable of stimulating autoreactive B cells and autoantibody production. We used DS-affinity proteomics to define the autoantigen-ome of lung fibroblasts and bioinformatics analyses to study the relationship between autoantigenic proteins and COVID-induced alterations. Using DS-affinity, we identified an autoantigen-ome of 408 proteins from human HFL1 cells, at least 231 of which are known autoAgs. Comparing with available COVID data, 352 proteins of the autoantigen-ome have thus far been found to be altered at protein or RNA levels in SARS-CoV-2 infection, 210 of which are known autoAgs. The COVID-altered proteins are significantly associated with RNA metabolism, translation, vesicles and vesicle transport, cell death, supramolecular fibrils, cytoskeleton, extracellular matrix, and interleukin signaling. They offer clues to neurological problems, fibrosis, smooth muscle dysfunction, and thrombosis. In particular, 150 altered proteins are related to the nervous system, including axon, myelin sheath, neuron projection, neuronal cell body, and olfactory bulb. An association with the melanosome is also identified. The findings from our study illustrate a connection between COVID infection and autoimmunity. The vast number of COVID-altered proteins with high intrinsic propensity to become autoAgs offers an explanation for the diverse autoimmune complications in COVID patients. The variety of autoAgs related to mRNA metabolism, translation, and vesicles suggests a need for long-term monitoring of autoimmunity in COVID. The COVID autoantigen atlas we are establishing provides a detailed molecular map for further investigation of autoimmune sequelae of the pandemic, such as “long COVID” syndrome.

Identification and validation of serum autoantibodies in children with B-cell acute lymphoblastic leukemia by serological proteome analysis

Background

B-cell acute lymphoblastic leukemia (B-ALL) is the most common malignancy of childhood. Even though significant progresses have been made in the treatment of B-ALL, some pediatric B-ALL have still poor prognosis. The identification of tumor autoantibodies may have utility in early cancer diagnosis and immunotherapy. In this study, we used serological proteome analysis (SERPA) to screen serum autoantibodies of pediatric B-ALL, aiming to contribute to the early detection of B-ALL in children.

Methods

The total proteins from three pooled B-ALL cell lines (NALM-6, REH and BALL-1 cells) were separated using two-dimensional gel electrophoresis (2-DE), which was followed by Western blot by mixed serum samples from children with B-ALL (n=20) or healthy controls (n=20). We analyzed the images of 2-D gel and Western blot by PDQuest software, and then identified the spots of immune responses in B-ALL samples compared with those in control samples. The proteins from spots were identified using mass spectrometry (MS). The autoantibodies against alpha-enolase (α-enolase) and voltage-dependent anion-selective channel protein 1 (VDAC1) were further validated in sera from another 30 children with B-ALL and 25 normal individuals by the use of enzyme-linked immunosorbent assay (ELISA). The protein expression levels of the candidate antigens α-enolase and VDAC1 in B-ALL were thoroughly studied by immunohistochemical analysis.

Results

Utilizing the SERPA approach, α-enolase and VDAC1 were identified as candidate autoantigens in children with B-ALL. The frequencies of autoantibodies against α-enolase and VDAC1 in children with B-ALL were 27% and 23% by using ELISA analysis, respectively, which were significantly higher than those in normal controls (4% and 0, p<0.05). Immunohistochemical analysis showed the expression of α-enolase and VDAC1 was positive in 95% and 85% of B-ALL patients, respectively, but negative expression levels were showed in the control group.

Conclusions

This study incidated that α-enolase and VDAC1 may be the autoantigens associated with B-ALL. Therefore, α-enolase and VDAC1 autoantibodies may be the potential serological markers for children with B-ALL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00184-w.

A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases

Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer. The autoantigen-ome is significantly associated with various processes in viral infections, such as translation, protein processing, and vesicle transport. Interestingly, the coding genes of autoAgs predominantly contain multiple exons with many possible alternative splicing variants, short transcripts, and short UTR lengths. These observations and the finding that numerous autoAgs involved in RNA-splicing showed altered expression in viral infections suggest that viruses exploit alternative splicing to reprogram host cell machinery to ensure viral replication and survival. While each cell type gives rise to a unique pool of autoAgs, 39 common autoAgs associated with cell stress and apoptosis were identified from all six cell types, with several being known markers of systemic autoimmune diseases. In particular, the common autoAg UBA1 that catalyzes the first step in ubiquitination is encoded by an X-chromosome escape gene. Given its essential function in apoptotic cell clearance and that X-inactivation escape tends to increase with aging, UBA1 dysfunction can therefore predispose aging women to autoimmune disorders. In summary, we propose a model of how viral infections lead to extensive molecular alterations and host cell death, autoimmune responses facilitated by autoAg-DS complexes, and ultimately autoimmune diseases. Overall, this master autoantigen-ome provides a molecular guide for investigating the myriad of autoimmune sequalae to COVID-19 and clues to the rare but reported adverse effects of the currently available COVID vaccines.

An autoantigen profile of human A549 lung cells reveals viral and host etiologic molecular attributes of autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae. Our work provides a rich resource for studies into “long COVID” and related autoimmune sequelae.

An Autoantigen-ome from HS-Sultan B-Lymphoblasts Offers a Molecular Map for Investigating Autoimmune Sequelae of COVID-19

To understand how COVID-19 may induce autoimmune diseases, we have been compiling an atlas of COVID-autoantigens (autoAgs). Using dermatan sulfate (DS) affinity enrichment of autoantigenic proteins extracted from HS-Sultan lymphoblasts, we identified 362 DS-affinity proteins, of which at least 201 (56%) are confirmed autoAgs. Comparison with available multi-omic COVID data shows that 315 (87%) of the 362 proteins are affected in SARS-CoV-2 infection via altered expression, interaction with viral components, or modification by phosphorylation or ubiquitination, at least 186 (59%) of which are known autoAgs. These proteins are associated with gene expression, mRNA processing, mRNA splicing, translation, protein folding, vesicles, and chromosome organization. Numerous nuclear autoAgs were identified, including both classical ANAs and ENAs of systemic autoimmune diseases and unique autoAgs involved in the DNA replication fork, mitotic cell cycle, or telomerase maintenance. We also identified many uncommon autoAgs involved in nucleic acid and peptide biosynthesis and nucleocytoplasmic transport, such as aminoacyl-tRNA synthetases. In addition, this study found autoAgs that potentially interact with multiple SARS-CoV-2 Nsp and Orf components, including CCT/TriC chaperonin, insulin degrading enzyme, platelet-activating factor acetylhydrolase, and the ezrin-moesin-radixin family. Furthermore, B-cell-specific IgM-associated ER complex (including MBZ1, BiP, heat shock proteins, and protein disulfide-isomerases) is enriched by DS-affinity and up-regulated in B-cells of COVID-19 patients, and a similar IgH-associated ER complex was also identified in autoreactive pre-B1 cells in our previous study, which suggests a role of autoreactive B1 cells in COVID-19 that merits further investigation. In summary, this study demonstrates that virally infected cells are characterized by alterations of proteins with propensity to become autoAgs, thereby providing a possible explanation for infection-induced autoimmunity. The COVID autoantigen-ome provides a valuable molecular resource and map for investigation of COVID-related autoimmune sequelae and considerations for vaccine design.

An Autoantigen Profile of Human A549 Lung Cells Reveals Viral and Host Etiologic Molecular Attributes of Autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae.

An Autoantigen Atlas from Human Lung HFL1 Cells Offers Clues to Neurological and Diverse Autoimmune Manifestations of COVID-19

COVID-19 is accompanied by a myriad of both transient and long-lasting autoimmune responses. Dermatan sulfate (DS), a glycosaminoglycan crucial for wound healing, has unique affinity for autoantigens (autoAgs) from apoptotic cells. DS-autoAg complexes are capable of stimulating autoreactive B cells and autoantibody production. Using DS affinity, we identified an autoantigenome of 408 proteins from human fetal lung fibroblast HFL11 cells, at least 231 of which are known autoAgs. Comparing with available COVID data, 352 proteins of the autoantigenome have thus far been found to be altered at protein or RNA levels in SARS-Cov-2 infection, 210 of which are known autoAgs. The COVID-altered proteins are significantly associated with RNA metabolism, translation, vesicles and vesicle transport, cell death, supramolecular fibrils, cytoskeleton, extracellular matrix, and interleukin signaling. They offer clues to neurological problems, fibrosis, smooth muscle dysfunction, and thrombosis. In particular, 150 altered proteins are related to the nervous system, including axon, myelin sheath, neuron projection, neuronal cell body, and olfactory bulb. An association with the melanosome is also identified. The findings from our study illustrate a strong connection between viral infection and autoimmunity. The vast number of COVID-altered proteins with propensity to become autoAgs offers an explanation for the diverse autoimmune complications in COVID patients. The variety of autoAgs related to mRNA metabolism, translation, and vesicles raises concerns about potential adverse effects of mRNA vaccines. The COVID autoantigen atlas we are establishing provides a detailed molecular map for further investigation of autoimmune sequelae of the pandemic.

Using Serological Proteome Analysis to Identify and Evaluate Anti-GRP78 Autoantibody as Biomarker in the Detection of Gastric Cancer

The serological biomarkers as noninvasive tests are the most promising way for diagnosing gastric cancer (GC). Serological proteome analysis (SERPA) has been used to identify tumor-associated antigens (TAAs) and the corresponding autoantibodies in many studies. To explore the relationship between gastric cancer development and serum autoantibody anti-GRP78 response found by the method of SERPA with the GC cell line AGS, we included two cohorts (133 GC and 133 normal individuals in test group; 300 GC and 300 normal individuals in validation group) of patients with newly diagnosed GC for verification. All GC and normal controls were matched by age and gender. The autoantibody levels of the sera in two cohorts were measured by immunoassay. Finally, the results showed that 78-kDa glucose-regulated protein (GRP78) was identified in GC by SERPA and the level of anti-GRP78 antibody in GC was higher than that in normal individuals in the two cohorts. Receiver operating characteristic (ROC) curve analysis showed similar diagnostic value of anti-GRP78 antibody in test group (AUC: 0.718) and validation group (AUC: 0.666) to identify GC patients from normal individuals. The AUCs of anti-GRP78 autoantibody in the diagnosis of GC patients with different clinical characteristic ranged from 0.676 to 0.773 in test group and ranged from 0.645 to 0.707 in validation group. In conclusion, autoantibody against GRP78 might be a potential diagnostic biomarker. Further large-scale studies will be needed to validate and improve its performance of the sensitivity, specificity, and AUC value in distinguishing GC from other diseases.

Predicting response and toxicity to PD-1 inhibition using serum autoantibodies identified from immuno-mass spectrometry

Background: Validated biomarkers are needed to identify patients at increased risk of immune-related adverse events (irAEs) to immune checkpoint blockade (ICB). Antibodies directed against endogenous antigens can change after exposure to ICB. Methods: Patients with different solid tumors stratified into cohorts received pembrolizumab every 3 weeks in a Phase II trial (INSPIRE study). Blood samples were collected prior to first pembrolizumab exposure (baseline) and approximately 7 weeks (pre-cycle 3) into treatment. In a discovery analysis, autoantibody target immuno-mass spectrometry was performed in baseline and pre-cycle 3 pooled sera of 24 INSPIRE patients based on clinical benefit (CBR) and irAEs. Results: Thyroglobulin (Tg) and thyroid peroxidase (TPO) were identified as the candidate autoantibody targets. In the overall cohort of 78 patients, the frequency of CBR and irAEs from pembrolizumab was 31% and 24%, respectively. Patients with an anti-Tg titer increase ≥1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without this increase in unadjusted, cohort adjusted, and multivariable models (OR=17.4, 95% CI 1.8-173.8, p=0.015). Similarly, patients with an anti-TPO titer ≥ 1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without the increase in unadjusted and cohort adjusted (OR=6.1, 95% CI 1.1-32.7, p=0.035) models. Further, the cohort adjusted analysis showed patients with anti-Tg titer greater than median (10.0 IU/mL) at pre-cycle 3 were more likely to have irAEs (OR=4.7, 95% CI 1.2-17.8, p=0.024). Patients with pre-cycle 3 anti-TPO titers greater than median (10.0 IU/mL) had a significant difference in overall survival (23.8 vs 11.5 months; HR=1.8, 95% CI 1.0-3.2, p=0.05). Conclusions: Patient increase ≥1.5x of anti-Tg and anti-TPO titers from baseline to pre-cycle 3 were associated with irAEs from pembrolizumab, and patients with elevated pre-cycle 3 anti-TPO titers had an improvement in overall survival.

Negative autoimmunity in a Spanish pediatric cohort suspected of type 1 diabetes, could it be monogenic diabetes?

Objective

Monogenic diabetes can be misdiagnosed as type 1 or type 2 diabetes in children. The right diagnosis is crucial for both therapeutic choice and prognosis and influences genetic counseling. The main objective of this study was to search for monogenic diabetes in Spanish pediatric patients suspected of type 1 diabetes with lack of autoimmunity at the onset of the disease. We also evaluated the extra value of ZnT8A in addition to the classical IAA, GADA and IA2A autoantibodies to improve the accuracy of type 1 diabetes diagnosis.

Methods

Four hundred Spanish pediatric patients with recent-onset diabetes (mean age 8.9 ± 3.9 years) were analyzed for IAA, GADA, IA2A and ZnT8A pancreatic-autoantibodies and HLA-DRB1 alleles. Patients without autoimmunity and those with only ZnT8A positive were screened for 12 monogenic diabetes genes by next generation sequencing.

Results

ZnT8A testing increased the number of autoantibody-positive patients from 373 (93.3%) to 377 (94.3%). An isolated positivity for ZnT8A allowed diagnosing autoimmune diabetes in 14.8% (4/27) of pediatric patients negative for the rest of the antibodies tested. At least 2 of the 23 patients with no detectable autoimmunity (8%) carried heterozygous pathogenic variants: one previously reported missense variant in the INS gene (p.Gly32Ser) and one novel frameshift variant (p.Val264fs) in the HNF1A gene. One variant of uncertain significance was also found. Carriers of pathogenic variants had HLA-DRB1 risk alleles for autoimmune diabetes and clinical characteristics compatible with type 1 diabetes except for the absence of autoimmunity.

Conclusion

ZnT8A determination improves the diagnosis of autoimmune diabetes in pediatrics. At least 8% of pediatric patients suspected of type 1 diabetes and with undetectable autoimmunity have monogenic diabetes and can benefit from the correct diagnosis of the disease by genetic study.

Autoantibody Biomarker Discovery in Primary Open Angle Glaucoma Using Serological Proteome Analysis (SERPA)

Glaucoma is an optic neurological disorder and the leading cause of irreversible blindness worldwide, with primary open angle glaucoma (POAG) as its most prevalent form. An early diagnosis of the disease is crucial to prevent loss of vision. Mechanisms behind glaucoma pathogenesis are not completely understood, but disease related alterations in the serological autoantibody profile indicate an immunologic component. These changes in immunoreactivity may serve as potential biomarkers for glaucoma diagnostics. We aimed to identify novel disease related autoantibodies targeting antigens in the trabecular meshwork as biomarkers to support early detection of POAG. We used serological proteome analysis (SERPA) for initial autoantibody profiling in a discovery sample set. The identified autoantibodies were validated by protein microarray analysis in a larger cohort with 60 POAG patients and 45 control subjects. In this study, we discovered CALD1, PGAM1, and VDAC2 as new biomarker candidates. With the use of artificial neural networks, the panel of these candidates and the already known markers HSPD1 and VIM was able to classify subjects into POAG patients and non-glaucomatous controls with a sensitivity of 81% and a specificity of 93%. These results suggest the benefit of these potential autoantibody biomarkers for utilization in glaucoma diagnostics.

Serum biomarkers for diagnosis and prediction of type 1 diabetes

Type 1 diabetes (T1D) culminates in the autoimmune destruction of the pancreatic βcells, leading to insufficient production of insulin and development of hyperglycemia. Serum biomarkers including a combination of glucose, glycated molecules, C-peptide, and autoantibodies have been well established for the diagnosis of T1D. However, these molecules often mark a late stage of the disease when ∼90% of the pancreatic insulin-producing β-cells have already been lost. With the prevalence of T1D increasing worldwide and because of the physical and psychological burden induced by this disease, there is a great need for prognostic biomarkers to predict T1D development or progression. This would allow us to identify individuals at high risk for early prevention and intervention. Therefore, considerable efforts have been dedicated to the understanding of disease etiology and the discovery of novel biomarkers in the last few decades. The advent of high-throughput and sensitive "-omics" technologies for the study of proteins, nucleic acids, and metabolites have allowed large scale profiling of protein expression and gene changes in T1D patients relative to disease-free controls. In this review, we briefly discuss the classical diagnostic biomarkers of T1D but mainly focus on the novel biomarkers that are identified as markers of β-cell destruction and screened with the use of state-of-the-art "-omics" technologies.

Autoantibodies as Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

Pediatric endocrine and metabolic diseases and proteomics

The principles of Predictive, Preventive and Personalized Medicine (PPPM) dictate the need to recognize individual susceptibility to disease in a timely fashion and to offer targeted preventive interventions and treatments. Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers, that will eventually promote the implementation of PPPM. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening to early recognition of specific at-risk populations for disease manifestations or complications in adult life and to monitoring of disease progression and response to treatment.

SIGNIFICANCE

Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers that will eventually lead to successful, targeted, patient-centric, individualized approach of each patient, as dictated by the principles of Predictive, Preventive and Personalized Medicine. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening, accurate diagnosis, early recognition of specific at-risk populations for the prevention of disease manifestation or future complications.

Tracking the Antibody Immunome in Type 1 Diabetes Using Protein Arrays

We performed an unbiased proteome-scale profiling of humoral autoimmunity in recent-onset type 1 diabetes (T1D) patients and nondiabetic controls against ∼10 000 human proteins using a Nucleic Acid Programmable Protein Array (NAPPA) platform, complemented by a knowledge-based selection of proteins from genes enriched in human pancreas. Although the global response was similar between cases and controls, we identified and then validated six specific novel T1D-associated autoantibodies (AAbs) with sensitivities that ranged from 16 to 27% at 95% specificity. These included AAbs against PTPRN2, MLH1, MTIF3, PPIL2, NUP50 (from NAPPA screening), and QRFPR (by targeted ELISA). Immunohistochemistry demonstrated that NUP50 protein behaved differently in islet cells, where it stained both nucleus and cytoplasm, compared with only nuclear staining in exocrine pancreas. Conversely, PPIL2 staining was absent in islet cells, despite its presence in exocrine cells. The combination of anti-PTPRN2, -MLH1, -PPIL2, and -QRFPR had an AUC of 0.74 and 37.5% sensitivity at 95% specificity. These data indicate that these markers behave independently and support the use of unbiased screening to find biomarkers because the majority was not predicted based on predicted abundance. Our study enriches the knowledge of the "autoantibody-ome" in unprecedented breadth and width.

The progress and potential of proteomic biomarkers for type 1 diabetes in children

INTRODUCTION

Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions. Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas. Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.

Early signs of disease in type 1 diabetes

As a severe chronic disease with long-term complications, type 1 diabetes (T1D) is a burden to the patients and their families as well as a challenge to the health care system. T1D is a heterogeneous disease with a variety of etiologies and a wide range in the rate of progression to the disease. In order to prevent and treat T1D it would be important to identify measures that could be used to predict and monitor disease progression, as well as to further understand the molecular mechanisms involved. During the past 20 yr since its initiation, the Finnish Diabetes Prediction and Prevention Project (DIPP) has collected longitudinal biological samples from children with a human leukocyte antigen gene-conferred risk of T1D. This large sample collection has provided detailed sample series that enable studies to map the progression from health to disease, as well as the healthy maturation of risk-matched children. The DIPP samples have been used in a large body of research to elucidate the factors involved in the development of T1D. Interestingly, results from recent studies exploiting omics platforms have revealed that signs of the disease process can be detected very early on, even prior to appearance of the first T1D-associated antibodies, which are currently considered the earliest indications of the emerging disease. Identification and validation of multi-modal molecular markers will we hope provide a means to subgroup the heterogeneous group of T1D patients and enable prediction, diagnosis, and monitoring of T1D. Discovery of such markers is important in the design and testing of prevention and therapies for T1D.

The Clinical Significance of Glycoprotein Phospholipase D Levels in Distinguishing Early Stage Latent Autoimmune Diabetes in Adults and Type 2 Diabetes

Autoantibodies have been widely used as markers of latent autoimmune diabetes in adults (LADA); however, the specificity and sensitivity of autoantibodies as markers of LADA are weak compared with those found in type 1 diabetes (T1DM). In this study, we aimed to identify other plasma proteins as potential candidates that can be used effectively to determine early stage LADA and type 2 diabetes (T2DM) to facilitate early diagnosis and treatment. These issues were addressed by studying new-onset ‘classic’ T1DM (n = 156), LADA (n = 174), T2DM (n = 195) and healthy cohorts (n = 166). Plasma samples were obtained from the four cohorts. We employed isobaric tag for relative and absolute quantitation (iTRAQ) together with liquid chromatography tandem mass spectrometry (LC-MS) to identify plasma proteins with significant changes in LADA. The changes were validated by Western blot and ELISA analyses. Among the four cohorts, 311 unique proteins were identified in three iTRAQ runs, with 157 present across the three data sets. Among them, 49/311 (16.0%) proteins had significant changes in LADA compared with normal controls, including glycoprotein phospholipase D (GPLD1), which was upregulated in LADA. Western blot and ELISA analyses showed that GPLD1 levels were higher in both LADA and T1DM cohorts than in both T2DM and healthy cohorts, while there were no significant differences in the plasma concentrations of GPLD1 between the LADA and T1DM cohorts. GPLD1 is implicated as a potential candidate plasma protein for determining early stage LADA and T2DM.

Anti-serum with anti-autoantibody activity decreases autoantibody-positive B lymphocytes and type 1 diabetes of female NOD mice

Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by an autoimmune-mediated loss of insulin secreting β-cells. Each B lymphocyte clone that escapes immune tolerance produces a specific antibody. No specific treatment against autoantibodies is available for autoimmune diseases. We have developed a strategy to produce an antiserum against autoantibodies for the treatment of T1DM. Non-obese diabetic (NOD) but not Balb/c mouse serum contains autoantibodies. Antisera were produced by immunizing Balb/c mice with affinity-purified IgG from NOD or BALB/c mice along with the immune adjuvant (hereafter, NIgG or BIgG, respectively). A bolus administration of NIgG significantly reduced serum autoantibodies, autoantibody-positive B lymphocytes in the spleens of NOD mice, mortality and morbidity of diabetes, blood glucose and islet immune infiltration, whereas it increased islet mass in NOD mice for at least 26 weeks. NIgG antiserum treatment has no significant effect on CD3(+), CD4(+) or CD8(+) T cells and B220(+) or CD19(+) B cells. BIgG also imparted a moderate therapeutic effect, although it was considerably lower than that of NIgG. NIgG did not cross-react with allogeneic serum. NIgG showed no effect on Balb/c mice. The results show the feasibility of producing antiserum against autoantibodies to prevent and treat autoimmune-induced T1DM with a single bolus administration.

An Optimized Fluorescence-Based Bidimensional Immunoproteomic Approach for Accurate Screening of Autoantibodies

Serological proteome analysis (SERPA) combines classical proteomic technology with effective separation of cellular protein extracts on two-dimensional gel electrophoresis, western blotting, and identification of the antigenic spot of interest by mass spectrometry. A critical point is related to the antigenic target characterization by mass spectrometry, which depends on the accuracy of the matching of antigenic reactivities on the protein spots during the 2D immunoproteomic procedures. The superimposition, based essentially on visual criteria of antigenic and protein spots, remains the major limitation of SERPA. The introduction of fluorescent dyes in proteomic strategies, commonly known as 2D-DIGE (differential in-gel electrophoresis), has boosted the qualitative capabilities of 2D electrophoresis. Based on this 2D-DIGE strategy, we have improved the conventional SERPA by developing a new and entirely fluorescence-based bi-dimensional immunoproteomic (FBIP) analysis, performed with three fluorescent dyes. To optimize the alignment of the different antigenic maps, we introduced a landmark map composed of a combination of specific antibodies. This methodological development allows simultaneous revelation of the antigenic, landmark and proteomic maps on each immunoblot. A computer-assisted process using commercially available software automatically leads to the superimposition of the different maps, ensuring accurate localization of antigenic spots of interest.

The beta-cell in type 1 diabetes: What have we learned from proteomic studies?

Pancreatic beta-cells have a crucial role in the regulation of blood glucose homeostasis by the production and secretion of insulin. In type 1 diabetes (T1D), an autoimmune reaction against the beta-cells together with the presence of inflammatory cytokines and ROS in the islets leads to beta-cell dysfunction and death. This review gives an overview of proteomic studies that lead to better understanding of beta-cell functioning in T1D. Protein profiling of isolated islets and beta-cell lines in health and T1D contributed to the unraveling of pathways involved in cytokine-induced cell death. In addition, by studying the serological proteome of T1D patients, new biomarkers and beta-cell autoantigens were discovered, which may improve screening tests and follow-up of T1D development. Interestingly, an important role for PTMs was demonstrated in the generation of beta-cell autoantigens. To conclude, proteomic techniques are of indispensable value to improve the knowledge on beta-cell function in T1D and the search toward therapeutic targets.

The pancreatic β-cell transcriptome and integrated-omics

PURPOSE OF REVIEW

β Cells represent one of many cell types in heterogeneous pancreatic islets and play the central role in maintaining glucose homeostasis, such that disrupting β-cell function leads to diabetes. This review summarizes the methods for isolating and characterizing β cells, and describes integrated 'omics' approaches used to define the β cell by its transcriptome and proteome.

RECENT FINDINGS

RNA sequencing and mass spectrometry-based protein identification have now identified RNA and protein profiles for mouse and human pancreatic islets and β cells, and for β-cell lines. Recent publications have outlined these profiles and, more importantly, have begun to assign the presence or absence of specific genes and regulatory molecules to β-cell function and dysfunction. Overall, researchers have focused on understanding the pathophysiology of diabetes by connecting genome, transcriptome, proteome, and regulatory RNA profiles with findings from genome-wide association studies.

SUMMARY

Studies employing these relatively new techniques promise to identify specific genes or regulatory RNAs with altered expression as β-cell function begins to deteriorate in the spiral toward the development of diabetes. The ultimate goal is to identify the potential therapeutic targets to prevent β-cell dysfunction and thereby better treat the individual with diabetes.

VIDEO ABSTRACT

http://links.lww.com/COE/A5.

Novel diabetes autoantibodies and prediction of type 1 diabetes

Autoantibodies are currently the most robust biomarkers of type 1 diabetes and are frequently used to establish entry criteria for the participation of genetically at-risk individuals in secondary prevention/intervention clinical trials. Since their original description almost 40 years ago, considerable efforts have been devoted toward identifying the precise molecular targets that are recognized. Such information can have significant benefit for developing improved metrics for identifying/stratifying of at-risk subjects, developing potential therapeutic targets, and advancing understanding of the pathophysiology of the disease. Currently, four major molecular targets ([pro]insulin, GAD65, IA-2, and ZnT8) have been confirmed, with approximately 94% of all subjects with a clinical diagnosis of type 1 diabetes expressing autoantibodies to at least one of these molecules at clinical onset. In this review, we summarize some of the salient properties of these targets that might contribute to their autoantigenicity and methods that have been used in attempts to identify new components of the humoral autoresponse.