Identification of diagnostic biomarkers used in the diagnosis of cardiovascular diseases and diabetes mellitus: A systematic review of quantitative studies

Author:

Wilson Megan1ORCID,Al‐Hamid Abdullah2,Abbas Ismail3,Birkett Jason1,Khan Iftikhar1,Harper Matthew4,Al‐Jumeily OBE Dhiya4,Assi Sulaf1

Affiliation:

1. Faculty of Science School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University Liverpool UK

2. Pharmacy Practice College of Clinical Pharmacy, King Faisal University AlAhsa Saudi Arabia

3. Faculty of Science Lebanese University Beirut

4. Faculty of Engineering and Technology School of Computer Science and Mathematics, Liverpool John Moores University Liverpool UK

Abstract

AbstractAimsTo 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 MethodsPapers 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.ResultsA 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.ConclusionsWhile 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.

Publisher

Wiley

Reference154 articles.

1. Organisation W.H.O.Cardiovascular Diseases.2023.https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1. Accessed 1 May 2023

2. Organisation W.H.O.Diabetes.2023.https://www.who.int/health-topics/diabetes#tab=tab_1. Accessed 1 May 2023

3. Machine learning-based heart disease diagnosis: A systematic literature review

4. Diabetes comorbidities in low- and middle-income countries: An umbrella review

5. Cardiovascular disease in low- and middle-income countries: an urgent priority

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