Aptamer-Based Proteomics Identifies Mortality-Associated Serum Biomarkers in Dialysis-Dependent AKI Patients

Circulating Proteins and Mortality in CKD: A Proteomics Study of the AASK and ARIC Cohorts

Rationale & Objective

Proteomics could provide pathophysiologic insight into the increased risk of mortality in patients with chronic kidney disease (CKD). This study aimed to investigate associations between the circulating proteome and all-cause mortality among patients with CKD.

Study Design

Observational cohort study.

Setting & Participants

Primary analysis in 703 participants in the African American Study of Kidney Disease and Hypertension (AASK) and validation in 1,628 participants with CKD in the Atherosclerosis Risk in Communities (ARIC) study who attended visit 5.

Exposure

Circulating proteins.

Outcome

All-cause mortality.

Analytical Approach

Among AASK participants, we evaluated the associations of 6,790 circulating proteins with all-cause mortality using multivariable Cox proportional hazards models. Proteins with significant associations were further studied in ARIC Visit 5 participants with CKD.

Results

In the AASK cohort, the mean age was 54.5 years, 271 (38.5%) were women, and the mean measured glomerular filtration rate (GFR) was 46 mL/min/1.73 m2. The median follow-up was 9.6 years, and 7 distinct proteins were associated with all-cause mortality at the Bonferroni-level threshold (P < 0.05 of the 6,790) after adjustment for demographics and clinical factors, including baseline measured estimated GFR and proteinuria. In the ARIC visit 5 cohort, the mean age was 77.2 years, 903 (55.5%) were women, the mean estimated GFR was 54 mL/min/1.73 m2 and median follow-up was 6.9 years. Of the 7 proteins found in AASK, 3 (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide) were available in the ARIC data, with all 3 significantly associated with death in ARIC.

Limitations

Possibility of unmeasured confounding. Cause of death was not known.

Conclusions

Using large-scale proteomic analysis, proteins were reproducibly associated with mortality in 2 cohorts of participants with CKD.

Plain-Language Summary

Patients with chronic kidney disease (CKD) have a high risk of premature death, with various pathophysiological processes contributing to this increased risk of mortality. This observational cohort study aimed to investigate the associations between circulating proteins and all-cause mortality in patients with CKD using large-scale proteomic analysis. The study analyzed data from the African American Study of Kidney Disease and Hypertension (AASK) study and validated the findings in the Atherosclerosis Risk in Communities (ARIC) Study. A total of 6,790 circulating proteins were evaluated in AASK, and 7 proteins were significantly associated with all-cause mortality. Three of these proteins (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide (BNP)) were also measured in ARIC and were significantly associated with death. Additional studies assessing biomarkers associated with mortality among patients with CKD are needed to evaluate their use in clinical practice.

IL-6 mediates the hepatic acute phase response after prerenal azotemia in a clinically defined murine model

Prerenal azotemia (PRA) is a major cause of acute kidney injury and uncommonly studied in preclinical models. We sought to develop and characterize a novel model of PRA that meets the clinical definition: acute loss of glomerular filtration rate (GFR) that returns to baseline with resuscitation. Adult male C57BL/6J wild-type (WT) and IL-6-/- mice were studied. Intraperitoneal furosemide (4 mg) or vehicle was administered at time = 0 and 3 h to induce PRA from volume loss. Resuscitation began at 6 h with 1 mL intraperitoneal saline for four times for 36 h. Six hours after furosemide administration, measured glomerular filtration rate was 25% of baseline and returned to baseline after saline resuscitation at 48 h. After 6 h of PRA, plasma interleukin (IL)-6 was significantly increased, kidney and liver histology were normal, kidney and liver lactate were normal, and kidney injury molecule-1 immunofluorescence was negative. There were 327 differentially regulated genes upregulated in the liver, and the acute phase response was the most significantly upregulated pathway; 84 of the upregulated genes (25%) were suppressed in IL-6-/- mice, and the acute phase response was the most significantly suppressed pathway. Significantly upregulated genes and their proteins were also investigated and included serum amyloid A2, serum amyloid A1, lipocalin 2, chemokine (C-X-C motif) ligand 1, and haptoglobin; hepatic gene expression and plasma protein levels were all increased in wild-type PRA and were all reduced in IL-6-/- PRA. This work demonstrates previously unknown systemic effects of PRA that includes IL-6-mediated upregulation of the hepatic acute phase response.NEW & NOTEWORTHY Prerenal azotemia (PRA) accounts for a third of acute kidney injury (AKI) cases yet is rarely studied in preclinical models. We developed a clinically defined murine model of prerenal azotemia characterized by a 75% decrease in measured glomerular filtration rate (GFR), return of measured glomerular filtration rate to baseline with resuscitation, and absent tubular injury. Numerous systemic effects were observed, such as increased plasma interleukin-6 (IL-6) and upregulation of the hepatic acute phase response.

The application of Aptamer in biomarker discovery

Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.

Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection

BACKGROUND

Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms.

METHODS

Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261).

RESULTS

We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p < 0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury.

CONCLUSIONS

Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease

BACKGROUND

We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD).

METHODS

Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays.

RESULTS

A total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all.

CONCLUSIONS

Intra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.

Interleukin-6 levels can be used to estimate cardiovascular and all-cause mortality risk in dialysis patients: A meta-analysis and a systematic review

BACKGROUND

Although previous studies have explored the correlation of interleukin (IL)-6 with mortality risk in dialysis patients, the findings have been conflicting. Hence, this meta-analysis aimed to comprehensively assess the use of IL-6 measurement for estimating cardiovascular mortality and all-cause mortality in dialysis patients.

METHODS

The Embase, PubMed, Web of Science, and MEDLINE databases were searched to identify relevant studies. After screening out the eligible studies, the data were extracted.

RESULTS

Twenty-eight eligible studies with 8370 dialysis patients were included. Pooled analyses revealed that higher IL-6 levels were related to increased cardiovascular mortality risk (hazard ratio [HR] = 1.55, 95% confidence interval [CI]: 1.20-1.90) and all-cause mortality risk (HR = 1.11, 95% CI: 1.05-1.17) in dialysis patients. Further subgroup analyses suggested that higher IL-6 levels were associated with elevated cardiovascular mortality in hemodialysis patients (HR = 1.59, 95% CI: 1.36-1.81) but not in peritoneal dialysis patients (HR = 1.56, 95% CI: 0.46-2.67). Moreover, sensitivity analyses indicated that the results were robust. Egger's test revealed potential publication bias among studies exploring the correlation of IL-6 levels with cardiovascular mortality (p = .004) and all-cause mortality (p < .001); however, publication bias was not observed when using Begg's test (both p > .05).

CONCLUSIONS

This meta-analysis reveals that higher IL-6 levels could indicate higher risks of cardiovascular mortality and all-cause mortality in dialysis patients. These findings suggest that monitoring IL-6 cytokine may help to enhance dialysis management and improve the general prognosis of patients.

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection

Background Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Methods Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). Results We demonstrate that COVID-AKI is associated with increased markers of tubular injury ( NGAL ) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2 , trefoil factor 3 , transmembrane emp24 domain-containing protein 10 , and cystatin-C indicating tubular dysfunction and injury. Conclusions Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection

Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Using measurements of ∼4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Nucleic Acid Nanotechnology for Diagnostics and Therapeutics in Acute Kidney Injury

Acute kidney injury (AKI) has impacted a heavy burden on global healthcare system with a high morbidity and mortality in both hospitalized and critically ill patients. However, there are still some shortcomings in clinical approaches for the disease to date, appealing for an earlier recognition and specific intervention to improve long-term outcomes. In the past decades, owing to the predictable base-pairing rule and highly modifiable characteristics, nucleic acids have already become significant biomaterials for nanostructure and nanodevice fabrication, which is known as nucleic acid nanotechnology. In particular, its excellent programmability and biocompatibility have further promoted its intersection with medical challenges. Lately, there have been an influx of research connecting nucleic acid nanotechnology with the clinical needs for renal diseases, especially AKI. In this review, we begin with the diagnostics of AKI based on nucleic acid nanotechnology with a highlight on aptamer- and probe-functionalized detection. Then, recently developed nanoscale nucleic acid therapeutics towards AKI will be fully elucidated. Furthermore, the strengths and limitations will be summarized, envisioning a wiser and wider application of nucleic acid nanotechnology in the future of AKI.

Diagnostic and Prognostic Protein Biomarkers of β-Cell Function in Type 2 Diabetes and Their Modulation with Glucose Normalization

Development of type-2 diabetes(T2D) is preceded by β-cell dysfunction and loss. However, accurate measurement of β-cell function remains elusive. Biomarkers have been reported to predict β-cell functional decline but require validation. Therefore, we determined whether reported protein biomarkers could distinguish patients with T2D (onset < 10-years) from controls. A prospective, parallel study in T2D (n = 23) and controls (n = 23) was undertaken. In T2D subjects, insulin-induced blood glucose normalization from baseline 7.6 ± 0.4 mmol/L (136.8 ± 7.2 mg/dL) to 4.5 ± 0.07 mmol/L (81 ± 1.2 mg/dL) was maintained for 1-h. Controls were maintained at 4.9 ± 0.1 mmol/L (88.2 ± 1.8 mg/dL). Slow Off-rate Modified Aptamer (SOMA) -scan plasma protein measurement determined a 43-protein panel reported as diagnostic and/or prognostic for T2D. At baseline, 9 proteins were altered in T2D. Three of 13 prognostic/diagnostic proteins were lower in T2D: Adiponectin (p < 0.0001), Endocan (p < 0.05) and Mast/stem cell growth factor receptor-Kit (KIT) (p < 0.01). Two of 14 prognostic proteins [Cathepsin-D (p < 0.05) and Cadherin-E (p < 0.005)], and four of 16 diagnostic proteins [Kallikrein-4 (p = 0.001), Aminoacylase-1 (p = 0.001), Insulin-like growth factor-binding protein-4 (IGFBP4) (p < 0.05) and Reticulon-4 receptor (RTN4R) (p < 0.001)] were higher in T2D. Protein levels were unchanged following glucose normalization in T2D. Our results suggest that a focused biomarker panel may be useful for assessing β-cell dysfunction and may complement clinical decision-making on insulin therapy. Unchanged post-glucose normalization levels indicate these are not acute-phase proteins or affected by glucose variability.

Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy

Acute kidney injury (AKI) requiring renal replacement therapy (RRT) is associated with increased incidence of dialysis dependence and portends high mortality in critically ill patients. At the early stage of RRT, serum metabolic biomarkers might differntiate patients with a high risk of mortality or permanent kidney injury from those who can recover. Serum samples from participants enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were collected on day 1 (n = 97) and day 8 (n = 105) of randomized RRT. The samples were further evaluated using LC/MS-based metabolic profiling. A model predicting mortality by day 8 was built from samples collected on day 1 and based on four metabolites with an area under the curve (AUC) of 0.641. A model most predictive of mortality by day 28 was built from the levels of 11 serum metabolites from day 8 with an AUC of 0.789. Both day 1 and day 8 samples had lower serum levels of 1-arachidonoyl-lysoPC and 1-eicosatetraenoyl-lysoPC (involved in anti-inflammatory processes) in the critically ill patients who died by day 8 or day 28. Higher levels of amino acids and amino acid metabolites in the day 8 model predicting < day 28 mortality may be indicative of muscle wasting. A kidney recovery biomarker panel based on the serum levels of three metabolites from day 8 samples with an AUC of 0.70 was devised. Serum metabolic profiling of AKI critically ill patients requiring RRT revealed predictive models of mortality based on observed differences in four serum metabolites at day 1 and 11 metabolites at day 8 which were predictive of mortality. Significant changes in the levels of these metabolites suggest links to inflammatory processes and/or muscle wasting.

Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients

BACKGROUND

AKI requiring dialysis (AKI-D) is associated with prolonged hospitalization, mortality, and progressive CKD among survivors. Previous studies have examined only select urine or serum biomarkers for predicting kidney recovery from AKI.

METHODS

Serum samples collected on day 8 of randomized RRT from 72 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the SOMAscan proteomic platform to profile 1305 proteins in each sample. Of these patients, 38 recovered kidney function and dialysis was discontinued, whereas another 34 patients remained on dialysis by day 28.

RESULTS

Differential serum levels of 119 proteins, with 53 higher and 66 lower, were detected in samples from patients who discontinued dialysis, compared with patients who remained on dialysis by day 28. Patients were classified into tertiles on the basis of SOMAscan protein measurements for the 25 proteins most differentially expressed. The association of serum levels of each protein with kidney recovery was further evaluated using logistic regression analysis. Higher serum levels of CXCL11, CXCL2/CXCL3, CD86, Wnt-7a, BTK, c-Myc, TIMP-3, CCL5, ghrelin, PDGF-C, survivin, CA2, IL-9, EGF, and neuregulin-1, and lower levels of soluble CXCL16, IL1RL1, stanniocalcin-1, IL-6, and FGF23 when classified in tertiles were significantly associated with better kidney recovery. This significant association persisted for each of these proteins after adjusting for potential confounding risk factors including age, sex, cardiovascular SOFA score, congestive heart failure, diabetes, modality of intensive dialysis treatment, cause of AKI, baseline serum creatinine, day 8 urine volume, and estimated 60-day mortality risk.

CONCLUSIONS

These results suggest concerted changes between survival-related proteins and immune-regulatory chemokines in regulating angiogenesis, endothelial and epithelial remodeling, and kidney cell regeneration, illustrating potential mechanisms of kidney recovery. Thus, this study identifies potential novel predictive biomarkers of kidney recovery in patients with AKI-D.

Advances in Aptamer-Based Biomarker Discovery

The discovery and identification of biomarkers promote the rational and fast development of medical diagnosis and therapeutics. Clinically, the application of ideal biomarkers still is limited due to the suboptimal technology in biomarker discovery. Aptamers are single-stranded deoxyribonucleic acid or ribonucleic acid molecules and can selectively bind to varied targets with high affinity and specificity. Compared with antibody, aptamers have desirable advantages, such as flexible design, easy synthesis and convenient modification with different functional groups. Currently, different aptamer-based technologies have been developed to facilitate biomarker discovery, especially CELL-SELEX and SOMAScan technology. CELL-SELEX technology is mainly used to identify cell membrane surface biomarkers of various cells. SOMAScan technology is an unbiased biomarker detection method that can analyze numerous and even thousands of proteins in complex biological samples at the same time. It has now become a large-scale multi-protein biomarker discovery platform. In this review, we introduce the aptamer-based biomarker discovery technologies, and summarize and highlight the discovered emerging biomarkers recently in several diseases.

Kidney to bone via bedside to bench…and back?

The rapid rise in circulating fibroblast growth factor 23 (FGF23) associated with kidney injury results in calcitriol deficiency, altered calcium homeostasis, and secondary hyperparathyroidism, and may contribute to cardiovascular complications and death. However, the mechanisms of increased FGF23 in states of kidney injury remain unclear. In this issue of the JCI, Simic et al. screened plasma taken from the renal vein of patients undergoing cardiac catheterization and identified glycerol-3-phosphate (G-3-P) as the most significant correlate of simultaneous arterial FGF23 levels. When G-3-P was administered to mice, FGF23 production increased in bone. In a series of elegant mouse studies, the authors discovered a pathway linking increased G-3-P to increased FGF23 via increases in lysophosphatidic acid (LPA), which activates the LPA receptor 1 in FGF23-secreting cells in the bone and bone marrow. Although the authors present human data that broadly support the results from the mouse models, further research is needed to determine whether targeting the G-3-P/FGF23 pathway has the potential to modify FGF23-related complications in the clinic.

Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach

Variable processing and storage of whole blood and/or plasma are potential confounders in biomarker development and clinical assays. The goal of the study was to investigate how pre-analytical variables impact the human plasma proteome. Whole blood obtained from 16 apparently healthy individuals was collected in six EDTA tubes and processed randomly under six pre-analytical variable conditions including blood storage at 0 °C or RT for 6 h (B6h0C or B6hRT) before processing to plasma, plasma storage at 4 °C or RT for 24 h (P24h4C or P24hRT), low centrifugal force at 1300 × g, (Low×g), and immediate processing to plasma under 2500 × g (control) followed by plasma storage at -80 °C. An aptamer-based proteomic assay was performed to identify significantly changed proteins (fold change ≥1.2, P < 0.05, and false discovery rate < 0.05) relative to the control from a total of 1305 proteins assayed. Pre-analytical conditions Low×g and B6h0C resulted in the most plasma proteome changes with 200 and 148 proteins significantly changed, respectively. Only 36 proteins were changed under B6hRT. Conditions P24h4C and P24hRT yielded changes of 28 and 75 proteins, respectively. The complement system was activated in vitro under the conditions B6hRT, P24h4C, and P24hRT. The results suggest that particular pre-analytical variables should be controlled for clinical measurement of specific biomarkers.

Application of Aptamer-based Hybrid Molecules in Early Diagnosis and Treatment of Diabetes Mellitus: From the Concepts Towards the Future

Aptamers have several positive advantages that made them eminent as a potential factor in diagnosing and treating diseases such as their application in prevention and treatment of diabetes. In this opinion-based mini-review article, we aimed to investigate the DNA and RNA-based hybrid molecules specifically aptamers and had a logical conclusion as a promising future perspective in early diagnosis and treatment of diabetes.