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Mini Article - (2023) Volume 14, Issue 3

Implications for Personalized Medicine and Circulating Glycaemia Biomarkers in Diabetes Treatment

John Miranda*
Department of Precision Medicine, Brazil
*Correspondence: John Miranda, Department of Precision Medicine, Brazil, Email:

Received: 01-Mar-2023, Manuscript No. Iptb-23-13610; Editor assigned: 03-Mar-2023, Pre QC No. Iptb-23-13610 (PQ); Reviewed: 16-Mar-2023, QC No. Iptb-23-13610; Revised: 20-Mar-2023, Manuscript No. Iptb-23-13610 (R); Published: 27-Mar-2023, DOI: 10.36648/2172- 0479.14.03.290


The personalized medicine model seeks to identify unique characteristics within each patient that can serve as a basis for disease characterization and specialized treatment rather than managing those with a specific diagnosis in accordance with established guidelines. Hemoglobin A1C, fructosamine, and anhydroglucitol are among the circulating biomarkers of glycaemia that are utilized in the medical management of diabetes and are discussed in this article. The areas in which biomarker results do not correlate with anticipated results based on actual mean glycaemia are the focus of the discussion. Inconstancy among genuine and expected aftereffects of the different biomarker tests addresses chances to distinguish already vague subcategories of diabetes and gatherings of patients that fit into these subcategories. Finally, research areas that would further advance the field of personalized diabetes medicine are suggested for these subcategories.


1, 5-Anhydroglucitol; Diabetes biomarkers; Glycation gap; Hemoglobin A1C variability; Hemoglobin glycation index; Personalized medicine


Illness the executives depend on normalized rules. This paradigm does not take into account the characteristics of each individual patient [1]. In contrast to this approach, personalized medicine makes an effort to comprehend patient characteristics as the disease progresses, with the idea that these characteristics influence the course of the disease and the most effective treatments [2]. This article reviews three circulating biomarkers of diabetes management and proposes using these biomarkers to define diabetes subgroups, despite the fact that there are certainly many factors in patients with diabetes that would lead to true personalization of therapy. The subgroups could then represent upcoming research projects that have the potential to advance personalized diabetes medicine.

A1C hemoglobin

HbA1c can be used as a reliable indicator of glycaemic control in the previous months, according to a number of studies. HbA1c is formed when glucose permanently attaches to hemoglobin A over the 120-day lifespan of the erythrocyte. The HbA1c test measures the ratio of hemoglobin HbA1c to total hemoglobin A. No diabetes patients have a normal level of less than 6%, while uncontrolled diabetes patients can have levels that are higher than 10%. The HbA1c test is the primary determinant of glucose control in virtually every clinical trial evaluating diabetes outcomes [3]. The Diabetes Control and Complications Trial was the first significant clinical trial. 1441 individuals with type 1 diabetes were divided into two groups and followed for an average of 6.5 years in this study. During that time, the conventional therapy group received standard care and maintained an HbA1c of 9.0%. An average HbA1c of 7.1% was achieved by the intensive therapy group on an aggressive insulin regimen. Retinopathy, nephropathy, and neuropathy were all reduced by 76%, 54%, and 60%, respectively, in the intensive therapy group. As a result, this clinical trial demonstrated a correlation between lowering HbA1c levels and reducing diabetes complications. The United Kingdom Prospective Diabetes Study4 was the second significant clinical trial. In this study, 3867 people with type 2 diabetes were randomly assigned to either a conventional diet-only or intensive group and followed for ten years. A similar reduction in micro-vascular complications and a separation in hemoglobin A1C between the two groups were observed [4]. A subsequent analysis revealed that a significant reduction in a number of macro vascular complications, including myocardial infarction, stroke, amputation, and heart failure, was associated with the benefit of a 1% reduction in HbA1c. Professional organizations were able to incorporate HbA1c targets into their diabetes guidelines on the basis of these trials. The European Association for the Study of Diabetes and the American Association of Clinical Endocrinologists have endorsed a stricter goal of HbA1c 6.5%, while the American Diabetes Association has advocated for a goal of HbA1c 7.0%. Trials have raised questions about how low the HbA1c target should be [5]. A particular intensive diabetes management strategy may not be beneficial to patients with advanced diabetes and cardiovascular disease. The HbA1c test has a number of drawbacks. The fact that the HbA1c test does not take into account glycaemic variability is a significant flaw. Derr and colleagues compared the self-monitoring of blood glucose (SMBG) data, calculated mean glucose levels, and measured HbA1c levels of 256 patients.9 some patients' SMBG data showed low glucose variability, while others had extremely high glucose variability [6]. The correlation between mean glucose levels and HbA1c was unaffected by this level of glucose variability, though. Erythrocyte and hemoglobin function is related to another flaw in the HbA1c test. The precision of the test relies on a steady 120- day normal erythrocyte life expectancy. Anemias that extend or abbreviate the typical life expectancy influence test unwavering quality by influencing the time period for erythrocyte glycosylation. When patients with variants of hemoglobin S, C, or E were tested, several laboratory procedures also produced unexpected results. Luckily, endeavours to normalize research center strategies have defeated this issue [7]. Only 5% of laboratories continue to employ techniques that significantly interfere with hemoglobinopathy. The different reference ranges that were given to each laboratory technique were a bigger problem than just that. For the same patients, different labs provided distinct HbA1c results. The initial DCCT-based high-performance liquid chromatography assay has been an important step in standardizing the various methods to a common reference, which has been achieved through the National Glycohemoglobin Standardization Program (NGSP).


Albumin is the most common of the gyrated serum proteins measured here. The best correlation between the fructosamine level and average glucose levels over the previous 10–14 days is found. In a study with 72 participants, Lindsey and colleagues found that weekly fructosamine testing, in addition to HbA1c testing, did not offer a clinical advantage over blood glucose monitoring alone. Clinically, fructosamine is utilized in patients who are known to have a condition that makes HbA1c testing temperamental or to distinguish transient changes in a patient's glucose control [8]. There is less fructosamine information when contrasted with HbA1c information, however numerical connection can be made between fructosamine, HbA1c, and normal glucose values. Fructosamine, HbA1c, and average glucose values were compared in two fascinating studies that were relevant to the idea of personalized medicine and were published by Cohen and colleagues. In these articles, the presence of a glycosylation hole (GG) is characterized as real HbA1c less HbA1c anticipated from fructosamine [9]. A wide GG distribution range was found when HbA1c and fructosamine were measured on the same sample of 153 individuals. A 1% increment in GG was related with a 2.9-overlap expansion in the gamble of nephropathy stage (p = .0014).20 Cohen and relates thusly assessed the expected heritability of GG, taking note of recently referred to prove for hereditary assurance of HbA1c level in solid endlessly twins with diabetes.18,21 Glycosylation hole was all the more firmly corresponded between monozygotic (r = .65) than dizygotic (r = .48) twins, and 69% of populace difference in GG was heritable [10].


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Citation: Miranda J (2023) Implications for Personalized Medicine and Circulating Glycaemia Biomarkers in Diabetes treatment. Transl Biomed, Vol. 14 No. 3:115