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Ferric particle-assisted LDI-MS platform for metabolic fingerprinting of diabetic retinopathy

  • Yu Liu ORCID logo , Yihan Wang , Xu Wan , Hongtao Huang , Jie Shen , Bin Wu , Lina Zhu , Beirui Wu , Wei Liu , Lin Huang EMAIL logo , Kun Qian EMAIL logo and Jing Ma ORCID logo EMAIL logo
Published/Copyright: November 30, 2023
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 62 Issue 5

Abstract

Objectives

To explore the metabolic fingerprints of diabetic retinopathy (DR) in individuals with type 2 diabetes using a newly-developed laser desorption/ionization mass spectrometry (LDI-MS) platform assisted by ferric particles.

Methods

Metabolic fingerprinting was performed using a ferric particle-assisted LDI-MS platform. A nested population-based case-control study was performed on 216 DR cases and 216 control individuals with type 2 diabetes.

Results

DR cases and control individuals with type 2 diabetes were comparable for a list of clinical factors. The newly-developed LDI-MS platform allowed us to draw the blueprint of plasma metabolic fingerprints from participants with and without DR. The neural network afforded diagnostic performance with an average area under curve value of 0.928 for discovery cohort and 0.905 for validation cohort (95 % confidence interval: 0.902–0.954 and 0.845–0.965, respectively). Tandem MS and Fourier transform ion cyclotron resonance MS with ultrahigh resolution identified seven specific metabolites that were significantly associated with DR in fully adjusted models. Of these metabolites, dihydrobiopterin, phosphoserine, N-arachidonoylglycine, and 3-methylhistamine levels in plasma were first reported to show the associations.

Conclusions

This work advances the design of metabolic analysis for DR and holds the potential to promise as an efficient tool for clinical management of DR.

Keywords: metabolic fingerprints; laser desorption/ionization mass spectrometry; diabetic retinopathy; biomarker; machine learning
Corresponding authors: Jing Ma, MD, PhD, Department of Endocrinology and Metabolism, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai 200127, P.R. China, E-mail: ; Kun Qian, PhD, School of Biomedical Engineering, Institute of Medical Robotics and Med X Research Institute, Shanghai Jiao Tong University, Shanghai 200030, P.R. China, E-mail: ; and Lin Huang, PhD, Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, P.R. China, E-mail:
Yu Liu, Yihan Wang and Xu Wan contributed equally to this work. Jing Ma, Kun Qian and Lin Huang share co-authorship.

Funding source: Shanghai Pujiang Program

Award Identifier / Grant number: 2019PJD027

Funding source: Joint Research Project of Pudong Health and Family Planning Commission of Shanghai

Award Identifier / Grant number: PW2023-D13

Funding source: The Major Chronic Non-communicable Disease Prevention and Control Research, National Key R&D Program of China

Award Identifier / Grant number: 2016YFC1305600

Award Identifier / Grant number: 2016YFC1305602

Funding source: Shanghai Municipal Health and Family Planning Commission grant.

Award Identifier / Grant number: 201740054

Funding source: Shanghai Institutions of Higher Learning

Award Identifier / Grant number: 2021-01-07-00-02-E00083

Funding source: Science and Technology Commission of Shanghai Municipality-Science and Technology Program

Award Identifier / Grant number: 20DZ2201500

Funding source: Ministry of Science and Technology of China

Award Identifier / Grant number: 2021YFF0703500

Award Identifier / Grant number: 2022YFE0103500

Funding source: Ministry of Education, Science and Technology Development Center-New Generation of Information Technology Innovation Program

Award Identifier / Grant number: 2019ITA01004

Funding source: Shanghai Health and Medical Development Foundation

Award Identifier / Grant number: DMRFP_I_06

Funding source: Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support

Award Identifier / Grant number: 20181807

Funding source: National Natural Science Foundation of China

Award Identifier / Grant number: 82001985

  1. Research ethics: This study was approved by the Institutional Review Board of Renji Hospital, Shanghai Jiao Tong University School of Medicine with all individuals giving informed consent (project number 2017[013]).

  2. Informed consent: Informed consent was obtained from all individuals included in this study.

  3. Author contributions: Yu Liu contributed to data interpretation and manuscript writing. Yihan Wang and Hongtao Huang contributed to the analysis and interpretation of data and led the data analysis. Xu Wan, Jie Shen, Bin Wu, Lina Zhu, Beirui Wu, Wei Luan, and Wei Liu contributed to the acquisition. Lin Huang, Kun Qian, and Jing Ma were involved in all aspects of the study, including study design and data collection, analysis, and interpretation. All authors made critical intellectual contributions to drafting and/or revising the manuscript and all approved the final version. Lin Huang, Kun Qian, and Jing Ma are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the accuracy of the data analysis.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: This work was sponsored by grant 20DZ2201500 from Science and Technology Commission of Shanghai Municipality-Science and Technology Program, grant 20181807 from Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support, grant 2019PJD027 from Shanghai Pujiang Program, DMRFP_I_06 from Shanghai Health and Medical Development Foundation, 2019ITA01004 from Ministry of Education, Science and Technology Development Center-New Generation of Information Technology Innovation Program, and grant PW2023-D13 Joint Research Project of Pudong Health and Family Planning Commission of Shanghai. This work is also sponsored by grant 82001985 from National Natural Science Foundation of China (NSFC), grant 2021YFF0703500 and 2022YFE0103500 from Ministry of Science and Technology of China, and grant 2021-01-07-00-02-E00083 from Shanghai Institutions of Higher Learning. This work is also sponsored by grant 2016YFC1305600 and 2016YFC1305602 from the Major Chronic Non-communicable Disease Prevention and Control Research, National Key R&D Program of China, and grant 201740054 from Shanghai Municipal Health and Family Planning Commission grant.

  6. Data availability: The raw data that support the findings of this study available from the corresponding author upon reasonable request for public readers due to the competing interest.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2023-0775).

Received: 2023-07-23
Accepted: 2023-10-27
Published Online: 2023-11-30
Published in Print: 2024-04-25

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2023-0775
Keywords for this article
metabolic fingerprints; laser desorption/ionization mass spectrometry; diabetic retinopathy; biomarker; machine learning

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. The International Consensus on ANA Patterns (ICAP): from conception to implementation
  4. Review
  5. Machine learning-based clinical decision support using laboratory data
  6. Mini Review
  7. Standardisation and harmonisation of thyroid-stimulating hormone measurements: historical, current, and future perspectives
  8. Opinion Papers
  9. Adopting the International Consensus on ANA Patterns (ICAP) classification for reporting: the experience of Italian clinical laboratories
  10. Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process
  11. Biological variation of inflammatory and iron metabolism markers in high-endurance recreational athletes; are these markers useful for athlete monitoring?
  12. General Clinical Chemistry and Laboratory Medicine
  13. A model for managing quality control for a network of clinical chemistry instruments measuring the same analyte
  14. Impact of Academia-Government Collaboration on Laboratory Medicine Standardization in South Korea: analysis of eight years creatinine proficiency testing experience
  15. Measurement uncertainty estimation of free drug concentrations in clinical laboratories using equilibrium dialysis
  16. Use of dried blood spots for monitoring inflammatory and nutritional biomarkers in the elderly
  17. S100B vs. “GFAP and UCH-L1” assays in the management of mTBI patients
  18. Evaluation of five multisteroid LC‒MS/MS methods used for routine clinical analysis: comparable performance was obtained for nine analytes
  19. Ensuring quality in 17OHP mass spectrometry measurement: an international study assessing isomeric steroid interference
  20. A novel LC-MS/MS-based assay for the simultaneous quantification of aldosterone-related steroids in human urine
  21. Clinical specificity of two assays for immunoglobulin kappa and lambda free light chains
  22. Reference Values and Biological Variations
  23. Estimation of the reference values and decision limits for growth hormone in newborns using dried blood spots
  24. Reference intervals of 24 trace elements in blood, plasma and erythrocytes for the Slovenian adult population
  25. Hematology and Coagulation
  26. Detection of blasts using flags and cell population data rules on Beckman Coulter DxH 900 hematology analyzer in patients with hematologic diseases
  27. Cancer Diagnostics
  28. Drainage fluid LDH and neutrophil to lymphocyte ratio as biomarkers for early detecting anastomotic leakage in patients undergoing colorectal surgery
  29. Cardiovascular Diseases
  30. Performance evaluation of a novel high-sensitivity cardiac troponin T assay: analytical and clinical perspectives
  31. Diabetes
  32. Ferric particle-assisted LDI-MS platform for metabolic fingerprinting of diabetic retinopathy
  33. Infectious Diseases
  34. Thrombopoietin levels in sepsis and septic shock – a systematic review and meta-analysis
  35. Effect of temperature on presepsin pre-analytical stability in biological fluids of preterm and term newborns
  36. Letters to the Editor
  37. Pseudohyperglycemia due to glucometer interference in galactosemia
  38. What could cause a false increase in serum C-reactive protein concentration?
  39. Discriminating signal from noise: the biological variation of circulating calprotectin in serum and plasma
  40. Diagnostic accuracy of adenosine deaminase for tuberculous pleural effusion: age does matter
  41. The role of the Brazilian proficiency testing/External Quality Assessment Program in the improvement of glycated hemoglobin measurement
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