Identification of hub genes related to the progression of type 1 diabetes by computational analysis

Osmosensor TMEM63B facilitates insulin secretion in pancreatic β-cells

Elevated glucose metabolism triggers two primary processes that lead to β-cell depolarization and insulin secretion: the closure of ATP-sensitive K+ channels via ATP-dependent mechanisms and the activation of mechanosensitive channels (MSCs) due to cell swelling. However, the identity of these MSCs remains unclear. In this study, we found that TMEM63B is a stretch-activated cation channel (SAC) crucial for regulating insulin secretion in response to elevated glucose levels. TMEM63B is abundantly expressed in β-cells, and its deletion impairs insulin secretion triggered by high glucose. High glucose levels typically increase Ca2+ influx and firing frequency in β-cells, a response largely eliminated when TMEM63B is deleted. Mechanistically, glucose metabolism induces cell swelling and activates TMEM63B, which, in turn, leads to β-cell depolarization and insulin secretion. In conclusion, our findings demonstrate that TMEM63B is an SAC essential for regulating insulin secretion in response to elevated glucose levels.

Identification of crucial extracellular genes as potential biomarkers in newly diagnosed Type 1 diabetes via integrated bioinformatics analysis

Purpose

In this study, we aimed to study the role of extracellular proteins as biomarkers associated with newly diagnosed Type 1 diabetes (NT1D) diagnosis and prognosis.

Patients and Methods

We retrieved and analyzed the GSE55098 microarray dataset from the Gene Expression Omnibus (GEO) database. Using R software, we screened out the extracellular protein-differentially expressed genes (EP-DEGs) through several protein-related databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to describe the role and function of these EP-DEGs. We used the STRING database to construct the interaction of proteins, Cytoscape software to visualize the protein-protein interaction (PPI) networks, and its plugin CytoHubba to identify the crucial genes between PPI networks. Finally, we used the comparative toxicogenomics database (CTD) to evaluate the connection between NT1D with the potential crucial genes and we validated our conclusions with another dataset (GSE33440) and some clinical samples.

Results

We identified 422 DEGs and 122 EP-DEGs from a dataset that includes (12) NT1D patients compared with (10) healthy people. Protein digestion and absorption, toll-like receptor signaling, and T cell receptor signaling were the most meaningful pathways defined by KEGG enrichment analyses. We recognized nine important extracellular genes: GZMB, CCL4, TNF, MMP9, CCL5, IFNG, CXCL1, GNLY, and LCN2. CTD analyses showed that LCN2, IFNG, and TNF had higher levels in NT1D and hypoglycemia; while TNF, IFNG and MMP9 increased in hyperglycemia. Further verification showed that LCN2, MMP9, TNF and IFNG were elevated in NT1D patients.

Conclusion

The nine identified key extracellular genes, particularly LCN2, IFNG, TNF, and MMP9, may be potential diagnostic biomarkers for NT1D. Our findings provide new insights into the molecular mechanisms and novel therapeutic targets of NT1D.

CCDC158: A novel regulator in renal proximal tubular endocytosis unveiled through exome sequencing and interactome analysis

Renal proximal tubular reabsorption of proteins and polypeptides is tightly regulated by a concerted action of the multi-ligand receptors with subsequent processing from the clathrin-coated pits to early/recycling and late endosomes and towards lysosomes. We performed whole exome-sequencing in a male patient from a consanguineous family, who presented with low- and intermediate molecular weight proteinuria, nephrocalcinosis and oligospermia. We identified a new potential player in tubular endocytosis, coiled-coil domain containing 158 (CCDC158). The variant in CCDC158 segregated with the phenotype and was also detected in a female sibling with a similar clinical kidney phenotype. We demonstrated the expression of this protein in kidney tubules and modeled its structure in silico. We hypothesized that the protein played a role in the tubular endocytosis by interacting with other endocytosis regulators, and used mass spectrometry to identify potential interactors. The role of CCDC158 in receptor-mediated endocytosis was further confirmed by transferrin and GST-RAP trafficking analyses in patient-derived proximal tubular epithelial cells. Finally, as CCDC158 is known to be expressed in the testis, the presence of oligospermia in the male sibling further substantiated the pathogenic role of the detected missense variant in the observed phenotype. In this study, we provide data that demonstrate the potential role of CCDC158 in receptor-mediated endocytosis, most likely by interaction with other endocytosis-related proteins that strongly correlate with the proximal tubular dysfunction phenotype as observed in the patients. However, more studies are needed to fully unravel the molecular mechanism(s) in which CCDC158 is involved.

Riemannian manifold-based geometric clustering of continuous glucose monitoring to improve personalized diabetes management

BACKGROUND

Continuous Glucose Monitoring (CGM) provides a detailed representation of glucose fluctuations in individuals, offering a rich dataset for understanding glycemic control in diabetes management. This study explores the potential of Riemannian manifold-based geometric clustering to analyze and interpret CGM data for individuals with Type 1 Diabetes (T1D) and healthy controls (HC), aiming to enhance diabetes management and treatment personalization.

METHODS

We utilized CGM data from publicly accessible datasets, covering both T1D individuals on insulin and HC. Data were segmented into daily intervals, from which 27 distinct glycemic features were extracted. Uniform Manifold Approximation and Projection (UMAP) was then applied to reduce dimensionality and visualize the data, with model performance validated through correlation analysis between Silhouette Score (SS) against HC cluster and HbA1c levels.

RESULTS

UMAP effectively distinguished between T1D on daily insulin and HC groups, with data points clustering according to glycemic profiles. Moderate inverse correlations were observed between SS against HC cluster and HbA1c levels, supporting the clinical relevance of the UMAP-derived metric.

CONCLUSIONS

This study demonstrates the utility of UMAP in enhancing the analysis of CGM data for diabetes management. We revealed distinct clustering of glycemic profiles between healthy individuals and diabetics on daily insulin indicating that in most instances insulin does not restore a normal glycemic phenotype. In addition, the SS quantifies day by day the degree of this continued dysglycemia and therefore potentially offers a novel approach for personalized diabetes care.

Serum and urinary levels of MIF, CD74, DDT and CXCR4 among patients with type 1 diabetes mellitus, type 2 diabetes and healthy individuals: Implications for further research

Background

Macrophage migration inhibitory factor (MIF) is a highly conserved cytokine with pleiotropic properties, mainly pro-inflammatory. MIF seems to exert its pro-inflammatory features by binding to its transmembrane cellular receptor CD74. MIF also has CXCR4, which acts as a co-receptor in this inflammatory process. Apart from MIF, D-dopachrome tautomerase (DDT) or MIF2, which belongs to the MIF superfamily, also binds to receptor CD74. Therefore, these molecules, MIF, CD74, DDT and CXCR4 are suggested to work together orchestrating an inflammatory process. Diabetes mellitus is characterised by chronic low-grade inflammation. Therefore, the aim of the present study was to evaluate serum and urinary levels of the aforementioned molecules among patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) and among healthy controls.

Methods

We enrolled 13 patients with T1DM, 74 patients with T2DM and 25 healthy individuals as controls. Levels of CD74, CXCR4, DDT, and MIF were measured using ELISA Kits according to the manufacturer's instructions.

Results

We documented increased serum MIF levels together with higher urinary CD74 levels among patients with T1DM, when compared to patients with T2DM and healthy adults. In particular, patients with T1DM showed significantly increased levels of MIF compared to T2DM (p = 0.011) and healthy controls (p = 0.0093). CD74 in urine were significantly higher in patients with T1DM compared to those affected with T2DM (p = 0.0302) and healthy group (p = 0.0099). On the contrary, serum CD74 were similar among the three groups. No statistical differences were identified in CXCR4 levels both in serum and in urine of all groups. Patients with T2DM and overweight/obesity had increased urinary levels of CD74, when compared to lean patients with T2DM.

Conclusion

The increased serum MIF levels and urinary CD74 levels among patients with T1DM may be attributed to the autoimmune milieu, which characterises patients with T1DM, when compared to patients with T2DM. These two findings merit further attention as they could pave the way for further research regarding the potential beneficial effects of inhibitors of MIF among patients with T1DM, especially in the early stages of T1DM. Finally, the role of inhibitors of MIF could be further explored in the context of obesity among patients with T2DM.

Identifying miRNA Signatures Associated with Pancreatic Islet Dysfunction in a FOXA2-Deficient iPSC Model

The pathogenesis of diabetes involves complex changes in the expression profiles of mRNA and non-coding RNAs within pancreatic islet cells. Recent progress in induced pluripotent stem cell (iPSC) technology have allowed the modeling of diabetes-associated genes. Our recent study using FOXA2-deficient human iPSC models has highlighted an essential role for FOXA2 in the development of human pancreas. Here, we aimed to provide further insights on the role of microRNAs (miRNAs) by studying the miRNA-mRNA regulatory networks in iPSC-derived islets lacking the FOXA2 gene. Consistent with our previous findings, the absence of FOXA2 significantly downregulated the expression of islet hormones, INS, and GCG, alongside other key developmental genes in pancreatic islets. Concordantly, RNA-Seq analysis showed significant downregulation of genes related to pancreatic development and upregulation of genes associated with nervous system development and lipid metabolic pathways. Furthermore, the absence of FOXA2 in iPSC-derived pancreatic islets resulted in significant alterations in miRNA expression, with 61 miRNAs upregulated and 99 downregulated. The upregulated miRNAs targeted crucial genes involved in diabetes and pancreatic islet cell development. In contrary, the absence of FOXA2 in islets showed a network of downregulated miRNAs targeting genes related to nervous system development and lipid metabolism. These findings highlight the impact of FOXA2 absence on pancreatic islet development and suggesting intricate miRNA-mRNA regulatory networks affecting pancreatic islet cell development.

The Effect of Vitamin D Deficiency on Immune-Related Hub Genes: A Network Analysis Associated With Type 1 Diabetes

Background Type 1 diabetes (T1D) is an autoimmune disorder that results in the destruction of pancreatic beta cells, causing a shortage of insulin secretion. The development of T1D is influenced by both genetic predisposition and environmental factors, such as vitamin D. This vitamin is known for its ability to regulate the immune system and has been associated with a decreased risk of T1D. However, the specific ways in which vitamin D affects immune regulation and the preservation of beta cells in T1D are not yet fully understood. Gaining a better understanding of these interactions is essential for identifying potential targets for preventing and treating T1D. Methods The analysis focused on two Gene Expression Omnibus (GEO) datasets, namely, GSE55098 and GSE50012, to detect differentially expressed genes (DEGs). Enrichr (Ma'ayan Laboratory, New York, NY) was used to perform enrichment analysis for the Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The Search Tool for the Retrieval of Interacting Genes 12.0 (STRING) database was used to generate a protein-protein interaction (PPI) network. The Cytoscape 3.10.1 (Cytoscape Team, San Diego, CA) was used to analyze the PPI network and discover the hub genes. Results The DEGs in both datasets were identified using the GEO2R tool, with a particular focus on genes exhibiting contrasting regulations. Enrichment analysis unveiled the participation of these oppositely regulated DEGs in processes relevant to the immune system. Cytoscape analysis of the PPI network revealed five hub genes, MNDA, LILRB2, FPR2, HCK, and FCGR2A, suggesting their potential role in the pathogenesis of T1D and the response to vitamin D. Conclusion The study elucidates the complex interaction between vitamin D metabolism and immune regulation in T1D. The identified hub genes provide important knowledge on the molecular pathways that underlie T1D and have the potential to be targeted for therapeutic intervention. This research underscores the importance of vitamin D in the immune system's modulation and its impact on T1D development.

In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Type 2 diabetes (T2D) and hypertension are global public health concerns and major metabolic disorders in humans. Experimental evidence indicates considerable hereditary influences on the etiology of T2D and hypertension, but the molecular basis of these diseases is still limited. Thus, the current study analyzed 185 (132 T2D and 53 hypertension) GWAS catalog datasets and identified 83 common genes linked to T2D and hypertension pathogenesis. These genes were further examined using various bioinformatics approaches to elucidate their molecular mechanisms underlying the pathophysiology of T2D and hypertension. Gene ontology (GO) analysis revealed the biological, cellular, and molecular functions of these genes, which were also linked to different T2D and hypertension pathways. Specifically, seven genes were found to be crucial for T2D, and nine were directly associated with hypertension. Protein-protein interaction (PPI) analysis identified 28 candidate genes and seven hub genes through 11 topological methods. Among 231 miRNAs, seven were significant in interacting with the hub genes, and nine transcription factors (TFs) out of 36 were linked to these hub genes. Additionally, two of the seven hub genes were downregulated by 43 FDA-approved drugs. These findings elucidate the molecular processes underlying T2D and hypertension, suggesting that targeting these genes could lead to future drug development and therapeutic strategies to treat T2D and hypertension.

A new perspective on the autophagic and non-autophagic functions of the GABARAP protein family: a potential therapeutic target for human diseases

Mammalian autophagy-related protein Atg8, including the LC3 subfamily and GABARAP subfamily. Atg8 proteins play a vital role in autophagy initiation, autophagosome formation and transport, and autophagy-lysosome fusion. GABARAP subfamily proteins (GABARAPs) share a high degree of homology with LC3 family proteins, and their unique roles are often overlooked. GABARAPs are as indispensable as LC3 in autophagy. Deletion of GABARAPs fails autophagy flux induction and autophagy lysosomal fusion, which leads to the failure of autophagy. GABARAPs are also involved in the transport of selective autophagy receptors. They are engaged in various particular autophagy processes, including mitochondrial autophagy, endoplasmic reticulum autophagy, Golgi autophagy, centrosome autophagy, and dorphagy. Furthermore, GABARAPs are closely related to the transport and delivery of the inhibitory neurotransmitter γ-GABAA and the angiotensin II AT1 receptor (AT1R), tumor growth, metastasis, and prognosis. GABARAPs also have been confirmed to be involved in various diseases, such as cancer, cardiovascular disease, and neurodegenerative diseases. In order to better understand the role and therapeutic potential of GABARAPs, this article comprehensively reviews the autophagic and non-autophagic functions of GABARAPs, as well as the research progress of the role and mechanism of GABARAPs in cancer, cardiovascular diseases and neurodegenerative diseases. It emphasizes the significance of GABARAPs in the clinical prevention and treatment of diseases, and may provide new therapeutic ideas and targets for human diseases. GABARAP and GABARAPL1 in the serum of cancer patients are positively correlated with the prognosis of patients, which can be used as a clinical biomarker, predictor and potential therapeutic target.

In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

Germline genetic variants are associated with development of insulin-dependent diabetes in cancer patients treated with immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICIs) have dramatically improved survival in patients with cancer but are often accompanied by severe immune-related adverse events (irAEs), which can sometimes be irreversible. Insulin-dependent diabetes is a rare, but life-altering irAE. Our purpose was to determine whether recurrent somatic or germline mutations are observed in patients who develop insulin-dependent diabetes as an irAE.

METHODS

We performed RNA and whole exome sequencing on tumors from 13 patients who developed diabetes due to ICI exposure (ICI-induced diabetes mellitus, ICI-DM) compared with control patients who did not develop diabetes.

RESULTS

In tumors from ICI-DM patients, we did not find differences in expression of conventional type 1 diabetes autoantigens, but we did observe significant overexpression of ORM1, PLG, and G6PC, all of which have been implicated in type 1 diabetes or are related to pancreas and islet cell function. Interestingly, we observed a missense mutation in NLRC5 in tumors of 9 of the 13 ICI-DM patients that was not observed in the control patients treated with the same drugs for the same cancers. Germline DNA from the ICI-DM patients was sequenced; all NLRC5 mutations were germline. The prevalence of NLRC5 germline variants was significantly greater than the general population (p=5.98×10^-6). Although NLRC5 is implicated in development of type 1 diabetes, germline NLRC5 mutations were not found in public databases from patients with type 1 diabetes, suggesting a different mechanism of insulin-dependent diabetes in immunotherapy-treated patients with cancer.

CONCLUSIONS

Validation of the NLRC5 mutation as a potential predictive biomarker is warranted, as it might improve patient selection for treatment regimens. Furthermore, this genetic alteration suggests potential mechanisms of islet cell destruction in the setting of checkpoint inhibitor therapy.

A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

Pancreatic islets comprise a group of cells that produce hormones regulating blood glucose levels. Particularly, the alpha and beta islet cells produce glucagon and insulin to stabilize blood glucose. When beta islet cells are dysfunctional, insulin is not secreted, inducing a glucose metabolic disorder. Identifying effective therapeutic targets against the disease is a complicated task and is not yet conclusive. To close the wide gap between understanding the molecular mechanism of pancreatic islet cells and providing effective therapeutic targets, we present a computational framework to identify potential therapeutic targets against pancreatic disorders. First, we downloaded three transcriptome expression profiling datasets pertaining to pancreatic islet cells (GSE87375, GSE79457, GSE110154) from the Gene Expression Omnibus database. For each dataset, we extracted expression profiles for two cell types. We then provided these expression profiles along with the cell types to our proposed constrained optimization problem of a support vector machine and to other existing methods, selecting important genes from the expression profiles. Finally, we performed (1) an evaluation from a classification perspective which showed the superiority of our methods against the baseline; and (2) an enrichment analysis which indicated that our methods achieved better outcomes. Results for the three datasets included 44 unique genes and 10 unique transcription factors (SP1, HDAC1, EGR1, E2F1, AR, STAT6, RELA, SP3, NFKB1, and ESR1) which are reportedly related to pancreatic islet functions, diseases, and therapeutic targets.

Prebiotic inulin nanocoating for pancreatic islet surface engineering

Pancreatic islet surface engineering has been proposed as an "easy-to-adopt" approach to enhance post-transplantation islet engraftment for treatment against diabetes. Inulin is an FDA-approved dietary prebiotic with reported anti-diabetic, anti-inflammatory, anti-hypoxic and pro-angiogenic properties. We therefore assessed whether inulin would be a viable option for islet surface engineering. Inulin was oxidized to generate inulin-CHO, which would bind to the cell membrane via covalent bond formation between -CHO and -NH₂ across the islet cell membrane. In vitro assessments demonstrated enhanced islet viability and better glucose-induced insulin secretion from inulin-coated (5 mg mL^-1) islets, which was accompanied by enhanced revascularization, shown as significantly enhanced tube formation and branching of islet endothelial MS1 cells following co-culture with inulin-coated islets. Reduction of cytokine-induced cell death was also observed from inulin-coated islets following exposure to pro-inflammatory cytokine LPS. LPS-induced ROS production was significantly dampened by 44% in inulin-coated islets when compared to controls. RNA-seq analysis of inulin-coated and control islets identified expression alterations of genes involved in islet function, vascular formation and immune regulation, supporting the positive impact of inulin on islet preservation. In vivo examination using streptozotocin (STZ)-induced hyperglycemic mice further showed moderately better maintained plasma glucose levels in mice received transplantation of inulin-coated islets, attributable to ameliorated CD45⁺ immune cell infiltration and improved in vivo graft vascularization. We therefore propose islet surface engineering with inulin as safe and beneficial, and further assessment is required to verify its applicability in clinical islet transplantation.

Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets

BACKGROUND

Type 1 diabetes (T1D) is a devastating disease with serious health complications. Early T1D biomarkers that could enable timely detection and prevention before the onset of clinical symptoms are paramount but currently unavailable. Despite their promise, omics approaches have so far failed to deliver such biomarkers, likely due to the fragmented nature of information obtained through the single omics approach. We recently demonstrated the utility of parallel multi-omics for the identification of T1D biomarker signatures. Our studies also identified challenges.

METHODS

Here, we evaluated a novel computational approach of data imputation and amplification as one way to overcome challenges associated with the relatively small number of subjects in these studies.

RESULTS

Using proprietary algorithms, we amplified our quadra-omics (proteomics, metabolomics, lipidomics, and transcriptomics) dataset from nine subjects a thousand-fold and analyzed the data using Ingenuity Pathway Analysis (IPA) software to assess the change in its analytical capabilities and biomarker prediction power in the amplified datasets compared to the original. These studies showed the ability to identify an increased number of T1D-relevant pathways and biomarkers in such computationally amplified datasets, especially, at imputation ratios close to the "golden ratio" of 38.2%:61.8%. Specifically, the Canonical Pathway and Diseases and Functions modules identified higher numbers of inflammatory pathways and functions relevant to autoimmune T1D, including novel ones not identified in the original data. The Biomarker Prediction module also predicted in the amplified data several unique biomarker candidates with direct links to T1D pathogenesis.

CONCLUSIONS

These preliminary findings indicate that such large-scale data imputation and amplification approaches are useful in facilitating the discovery of candidate integrated biomarker signatures of T1D or other diseases by increasing the predictive range of existing data mining tools, especially when the size of the input data is inherently limited.

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.

Pancreatic INS-1 β-Cell Response to Thapsigargin and Rotenone: A Comparative Proteomics Analysis Uncovers Key Pathways of β-Cell Dysfunction

Insulin-secreting β-cells in the pancreatic islets are exposed to various endogenous and exogenous stressing conditions, which may lead to β-cell dysfunction or apoptosis and ultimately to diabetes mellitus. However, the detailed molecular mechanisms underlying β-cell's inability to survive under severe stresses remain to be explored. This study used two common chemical stressors, thapsigargin and rotenone, to induce endoplasmic reticulum (ER) and mitochondria stress in a rat insuloma INS-1 832/13 β-cell line, mimicking the conditions experienced by dysfunctional β-cells. Proteomic changes of cells upon treatment with stressors at IC₅₀ were profiled with TMT-based quantitative proteomics and further verified using label-free quantitive proteomics. The differentially expressed proteins under stress conditions were selected for in-depth bioinformatic analysis. Thapsigargin treatment specifically perturbed unfolded protein response (UPR) related pathways; in addition, 58 proteins not previously linked to the UPR related pathways were identified with consistent upregulation under stress induced by thapsigargin. Conversely, rotenone treatment resulted in significant proteome changes in key mitochondria regulatory pathways such as fatty acid β-oxidation, cellular respiration, citric acid cycle, and respiratory electron transport. Our data also demonstrated that both stressors increased reactive oxygen species production and depleted adenosine triphosphate synthesis, resulting in significant dysregulation of oxidative phosphorylation signaling pathways. These novel dysregulated proteins may suggest an alternative mechanism of action in β-cell dysfunction and provide potential targets for probing ER- and mitochondria stress-induced β-cell death.