Metabolomics Profiles Associated with Diabetic Retinopathy
By LabMedica International staff writers Posted on 16 Nov 2020 |

Image: The AbsoluteIDQ p180 kit provides scientists with highly reproducible metabolomics data to confidently obtain detailed knowledge about the metabolic phenotypes in their studies (Photo courtesy of BIOCRATES Life Sciences).
Diabetic retinopathy (DR), like diabetic neuropathy and nephropathy, is a common complication of diabetes. It is the leading cause of loss of vision in diabetic patients. Long-standing disease, along with hyperglycemia, hyperlipidemia, hypertension, and genetic factors, is a major risk factor of diabetes retinopathy.
Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease progression. Quantitative analyses of small-molecule metabolites in biological specimens such as blood and urine can be performed due to the rapid advances in metabolomics.
Medical Scientists at the Chungbuk National University College of Medicine (Cheongju, Republic of Korea) included in a study 317 type 2 diabetes (T2D) patients of which 143 non-DR (NDR) patients, 123 non- proliferative DR (NPDR) patients, and 51 proliferative-DR (PDR) patients. Gender, age, height, weight, body mass index (BMI), and HbA1c, glucose, and creatinine levels of all patients were recorded.
The serum samples of the T2D patients were analyzed using a targeted metabolomics approach. To quantify the metabolites, liquid chromatography (LC) and flow-injection analysis (FIA)–mass spectrometry (MS) were performed using the AbsoluteIDQ p180 Kit (BIOCRATES Life Sciences AG, Innsbruck, Austria). The serum samples were analyzed using the API 4000 QTRAP LC/MS/MS system (Applied Biosystems, Foster City, CA, USA) and the Agilent 1200 HPLC system (Agilent Technologies, Santa Clara, CA, USA).
The investigators reported that the concentrations of 62 metabolites of the NDR versus DR group, 53 metabolites of the NDR versus NPDR group, and 30 metabolites of the NDR versus PDR group were found to be significantly different. Sixteen metabolites were selected as specific metabolites common to NPDR and PDR. Among them, three metabolites including total dimethylarginine, tryptophan, and kynurenine were potential makers of DR progression in T2D patients. Additionally, several metabolites such as carnitines, several amino acids, and phosphatidylcholines also showed a biomarker potential.
The authors concluded that they had revealed via comprehensive metabolomics profiling using a high-throughput platform, several metabolites associated with DR. These new DR-related metabolites should be considered in the study of the mechanism behind the initiation and progression of DR in T2D patients. The study was published on October 29, 2020 in the journal PLOS ONE.
Related Links:
Chungbuk National University College of Medicine
BIOCRATES Life Sciences
Applied Biosystems
Agilent Technologies
Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease progression. Quantitative analyses of small-molecule metabolites in biological specimens such as blood and urine can be performed due to the rapid advances in metabolomics.
Medical Scientists at the Chungbuk National University College of Medicine (Cheongju, Republic of Korea) included in a study 317 type 2 diabetes (T2D) patients of which 143 non-DR (NDR) patients, 123 non- proliferative DR (NPDR) patients, and 51 proliferative-DR (PDR) patients. Gender, age, height, weight, body mass index (BMI), and HbA1c, glucose, and creatinine levels of all patients were recorded.
The serum samples of the T2D patients were analyzed using a targeted metabolomics approach. To quantify the metabolites, liquid chromatography (LC) and flow-injection analysis (FIA)–mass spectrometry (MS) were performed using the AbsoluteIDQ p180 Kit (BIOCRATES Life Sciences AG, Innsbruck, Austria). The serum samples were analyzed using the API 4000 QTRAP LC/MS/MS system (Applied Biosystems, Foster City, CA, USA) and the Agilent 1200 HPLC system (Agilent Technologies, Santa Clara, CA, USA).
The investigators reported that the concentrations of 62 metabolites of the NDR versus DR group, 53 metabolites of the NDR versus NPDR group, and 30 metabolites of the NDR versus PDR group were found to be significantly different. Sixteen metabolites were selected as specific metabolites common to NPDR and PDR. Among them, three metabolites including total dimethylarginine, tryptophan, and kynurenine were potential makers of DR progression in T2D patients. Additionally, several metabolites such as carnitines, several amino acids, and phosphatidylcholines also showed a biomarker potential.
The authors concluded that they had revealed via comprehensive metabolomics profiling using a high-throughput platform, several metabolites associated with DR. These new DR-related metabolites should be considered in the study of the mechanism behind the initiation and progression of DR in T2D patients. The study was published on October 29, 2020 in the journal PLOS ONE.
Related Links:
Chungbuk National University College of Medicine
BIOCRATES Life Sciences
Applied Biosystems
Agilent Technologies
Latest Pathology News
- AI Performs Virtual Tissue Staining at Super-Resolution
- AI-Driven Preliminary Testing for Pancreatic Cancer Enhances Prognosis
- Cancer Chip Accurately Predicts Patient-Specific Chemotherapy Response
- Clinical AI Solution for Automatic Breast Cancer Grading Improves Diagnostic Accuracy
- Saliva-Based Testing to Enable Early Detection of Cancer, Heart Disease or Parkinson’s
- Advances in Monkeypox Virus Diagnostics to Improve Management of Future Outbreaks
- Nanoneedle-Studded Patch Could Eliminate Painful and Invasive Biopsies
- AI Cancer Classification Tool to Drive Targeted Treatments
- AI-Powered Imaging Enables Faster Lung Disease Treatment
- New Laboratory Method Speeds Diagnosis of Rare Genetic Disease
- New Technology Autonomously Detects AI Hallucinations in Digital Pathology
- Novel Algorithm Rapidly Identifies Cell Types to Improve Cancer Diagnosis
- AI Method Speeds Up Cancer Tracking Using Blood Tests
- New AI Tool Improves Blood Cancer Diagnosis
- Novel Platform Technology Predicts Diseases by Early Detection of Aging Signals in Liver Tissue
- AI Model Detects More Than 170 Cancer Types
Channels
Molecular Diagnostics
view channel
Blood Test Could Predict Likelihood of Breast Cancer Spreading to The Bone
When breast cancer spreads to other parts of the body, it becomes secondary or metastatic breast cancer—a stage that, while treatable, is currently incurable. The bone is the most common site for this... Read more
New Infectious Disease Analytics Platform Speeds Up Clinical Decision-Making at POC
During the COVID-19 pandemic, the importance of accurate and timely interpretation of diagnostic data became evident in shaping both public health strategies and clinical outcomes. As the world now grapples... Read moreHematology
view channel
Disposable Cartridge-Based Test Delivers Rapid and Accurate CBC Results
Complete Blood Count (CBC) is one of the most commonly ordered lab tests, crucial for diagnosing diseases, monitoring therapies, and conducting routine health screenings. However, more than 90% of physician... Read more
First Point-of-Care Heparin Monitoring Test Provides Results in Under 15 Minutes
Heparin dosing requires careful management to avoid both bleeding and clotting complications. In high-risk situations like extracorporeal membrane oxygenation (ECMO), mortality rates can reach about 50%,... Read moreImmunology
view channel
Blood Test Detects Organ Rejection in Heart Transplant Patients
Following a heart transplant, patients are required to undergo surgical biopsies so that physicians can assess the possibility of organ rejection. Rejection happens when the recipient’s immune system identifies... Read more
Liquid Biopsy Approach to Transform Diagnosis, Monitoring and Treatment of Lung Cancer
Lung cancer continues to be a major contributor to cancer-related deaths globally, with its biological complexity and diverse regulatory processes making diagnosis and treatment particularly difficult.... Read more
Computational Tool Exposes Hidden Cancer DNA Changes Influencing Treatment Resistance
Structural changes in tumor DNA are among the most damaging genetic alterations in cancer, yet they often go undetected, particularly when tissue samples are degraded or of low quality. These hidden genomic... Read moreMicrobiology
view channel
Viral Load Tests Can Help Predict Mpox Severity
Mpox is a viral infection that causes flu-like symptoms and a characteristic rash, which evolves significantly over time and varies between patients. The disease spreads mainly through direct contact with... Read more
Gut Microbiota Analysis Enables Early and Non-Invasive Detection of Gestational Diabetes
Gestational diabetes mellitus is a common metabolic disorder marked by abnormal glucose metabolism during pregnancy, typically emerging in the mid to late stages. It significantly heightens the risk of... Read morePathology
view channel
AI Performs Virtual Tissue Staining at Super-Resolution
Conventional histopathology, essential for diagnosing various diseases, typically involves chemically staining tissue samples to reveal cellular structures under a microscope. This process, known as “histochemical... Read more
AI-Driven Preliminary Testing for Pancreatic Cancer Enhances Prognosis
Pancreatic cancer poses a major global health threat due to its high mortality rate, with 467,409 deaths and 510,992 new cases reported worldwide in 2022. Often referred to as the "king" of all cancers,... Read more
Cancer Chip Accurately Predicts Patient-Specific Chemotherapy Response
Esophageal adenocarcinoma (EAC), one of the two primary types of esophageal cancer, ranks as the sixth leading cause of cancer-related deaths worldwide and currently lacks effective targeted therapies.... Read more
Clinical AI Solution for Automatic Breast Cancer Grading Improves Diagnostic Accuracy
Labs that use traditional image analysis methods often suffer from bottlenecks and delays. By digitizing their pathology practices, labs can streamline their work, allowing them to take on larger caseloads... Read moreTechnology
view channel
Inexpensive DNA Coated Electrode Paves Way for Disposable Diagnostics
Many people around the world still lack access to affordable, easy-to-use diagnostics for diseases like cancer, HIV, and influenza. Conventional sensors, while accurate, often rely on expensive equipment... Read more
New Miniature Device to Transform Testing of Blood Cancer Treatments
Chimeric antigen receptor (CAR) T cell therapy has emerged as a groundbreaking treatment for blood cancers like leukemia, offering hope to patients when other treatments fail. However, despite its promise,... Read moreIndustry
view channel
AMP Releases Best Practice Recommendations to Guide Clinical Laboratories Offering HRD Testing
Homologous recombination deficiency (HRD) testing identifies tumors that are unable to effectively repair DNA damage through the homologous recombination repair pathway. This deficiency is often linked... Read more