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Wilson, M, Al‐Hamid, A, Abbas, I, Birkett, JW, Khan, I, Harper, M, Al‐Jumeily, D and Assi, S (2024) Identification of diagnostic biomarkers used in the diagnosis of cardiovascular diseases and diabetes mellitus: A systematic review of quantitative studies. Diabetes, Obesity and Metabolism. ISSN 1462-8902
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2024. M Wilson. Identification of diagnostic biomarkers used in the diagnosis of CVD and DM, A systematic review.pdf - Published Version Available under License Creative Commons Attribution. Download (979kB) | Preview |
Abstract
Aims
To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low- and middle-income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training.
Materials and Methods
Papers were sourced from six databases: the British Nursing Index, Google Scholar, PubMed, Sage, Science Direct and Scopus. Articles published between January 2002 and January 2023 were systematically reviewed by three reviewers and appropriate search terms and inclusion/exclusion criteria were applied.
Results
A total of 18 studies were yielded, as well as 234 diagnostic biomarkers (74 for CVD and 160 for DM). Primary biomarkers for the diagnosis of CVDs included growth differentiation factor 15 and neurogenic locus notch homologue protein 1 (Notch1). For the diagnosis of DM, alpha-2-macroglobulin, C-peptides, isoleucine, glucose, tyrosine, linoleic acid and valine were frequently reported across the included studies. Advanced analytical techniques, such as liquid chromatography mass spectrometry, enzyme-linked immunosorbent assays and vibrational spectroscopy, were also repeatedly reported in the included studies and were utilized in combination with traditional and alternative matrices such as fingernails, hair and saliva.
Conclusions
While advanced analytical techniques are expensive, laboratories in LMICs should carry out a cost–benefit analysis of their use. Alternatively, laboratories may want to explore emerging techniques such as infrared, Fourier transform-infrared and near-infrared spectroscopy, which allow sensitive noninvasive analysis.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 1103 Clinical Sciences; Endocrinology & Metabolism |
| Subjects: | Q Science > QP Physiology R Medicine > RS Pharmacy and materia medica |
| Divisions: | Computer Science and Mathematics Pharmacy and Biomolecular Sciences |
| Publisher: | Wiley |
| Date of acceptance: | 25 March 2024 |
| Date of first compliant Open Access: | 22 April 2024 |
| Date Deposited: | 22 Apr 2024 11:45 |
| Last Modified: | 22 Apr 2024 11:45 |
| DOI or ID number: | 10.1111/dom.15593 |
| URI: | https://ljmu-9.eprints-hosting.org/id/eprint/23101 |
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