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Background:
Review

Leukocyte Telomere Length as a Molecular Biomarker of Coronary Heart Disease

by
Olga V. Zimnitskaya
1,*,
Marina M. Petrova
1,
Natalia V. Lareva
2,
Marina S. Cherniaeva
3,
Mustafa Al-Zamil
4,
Anastasia E. Ivanova
5 and
Natalia A. Shnayder
1,5,*
1
Department of Outpatient Therapy and General Practice with Course of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
2
Department of Therapy, Faculty of Postgraduate Education, Chita State Medical Academy, 672000 Chita, Russia
3
Department of Internal and Preventive Medicine, Central State Medical Academy of the Presidential Administration, 121359 Moscow, Russia
4
Department of Physiotherapy, Faculty of Continuing Medical Education, Peoples’ Friendship University of Russia, 117198 Moscow, Russia
5
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, Institute of Personalized Psychiatry and Neurology, 192019 St. Petersburg, Russia
*
Authors to whom correspondence should be addressed.
Genes 2022, 13(7), 1234; https://doi.org/10.3390/genes13071234
Submission received: 7 June 2022 / Revised: 4 July 2022 / Accepted: 9 July 2022 / Published: 12 July 2022
(This article belongs to the Special Issue The Stability and Evolution of Genes and Genomes)
Browse Figures
Versions Notes

Abstract

:
Background. This work is a review of preclinical and clinical studies of the role of telomeres and telomerase in the development and progression of coronary heart disease (CHD). Materials and methods. A search for full-text publications (articles, reviews, meta-analyses, Cochrane reviews, and clinical cases) in English and Russian was carried out in the databases PubMed, Oxford University Press, Scopus, Web of Science, Springer, and E-library electronic library using keywords and their combinations. The search depth is 11 years (2010–2021). Results. The review suggests that the relative leukocyte telomere length (LTL) is associated with the development of socially significant and widespread cardiovascular diseases such as CHD and essential hypertension. At the same time, the interests of researchers are mainly focused on the study of the relative LTL in CHD. Conclusions. Despite the scientific and clinical significance of the analyzed studies of the relative length of human LTL as a biological marker of cardiovascular diseases, their implementation in real clinical practice is difficult due to differences in the design and methodology of the analyzed studies, as well as differences in the samples by gender, age, race, and ethnicity. The authors believe that clinical studies of the role of the relative length of leukocyte telomeres in adult patients with coronary heart disease are the most promising and require large multicenter studies with a unified design and methodology.

1. Introduction

Cardiovascular diseases (CVDs) are prevalent worldwide. In Europe, there were 19.9 million new cases of cardiovascular disease in 2017. There were 2.5 million new cases of CVD in Germany, 1.115 million in France, and 1.209 million new cases of CVD in the United Kingdom [1]. CVDs are the leading cause of death in most European countries [1] and Russia [2]. In European countries, CVDs cause about 2.2 million female and 1.9 million male deaths per year [1], and in Russia, the mortality rate from CVDs is about 938,500 per year [3]. Coronary artery disease (CAD) or coronary heart disease (CHD) are responsible for over 50% of CVD deaths in Russia [2,3] and cause about 40% of CVD deaths in Europe [1].
Genetic factors have a significant impact on the risk of CVD. A history of CVD increases their future risk from 40% to 75% depending on the degree of the relationship [4]. Aging is a major risk factor for CVDs and cerebrovascular diseases but it has been established that people age at different rates. Therefore, aging is characterized by chronological and biological aging. Chronological aging refers to the time elapsed since a person was born, and biological aging refers to the decline in the function of a person’s tissues and organs. In people who age normally, chronological age is equated with biological age [5]. In 2008, Nisson et al. [6] formulated the concept of early vascular aging (EVA), according to which the biological age of a person depends on the age of his or her blood vessels, and persons with EVA syndrome due to early vascular aging have an increased risk of developing CVDs and their complications. There is no clear list of EVA criteria, but some authors refer to physiological biomarkers of EVA as increased arterial vascular wall stiffness (arterial stiffness) assessed by pulse wave velocity or by calculation of the cardiovascular ankle index; a thickening of the intima-media complex; endothelial dysfunction [7,8,9]; the presence of atherosclerotic plaques in arteries; and the deposition of calcium phosphate crystals in arterial intima [10,11].
Deoxyribonucleic acid (DNA) methylation and telomere shortening are considered potential molecular biomarkers of EVA [5]. In a progressively aging world population, early diagnosis based on the development and implementation into real clinical practice of such molecular biomarkers is very important, as it may allow effective identification of people with a high risk of EVA in different climatic–geographical regions and racial and ethnic groups. Such a personalized strategy is expected to reduce the socio-economic burden of age-associated diseases including CVDs in general but in particular CAD.
In recent years, blood leukocyte telomere length (LTL) has been considered a “mitotic clock” fixing human biological age [12] and as a potential molecular biomarker of EVA, but research in this area is ongoing and no unequivocal decision on this issue has been made yet [13].
Also, as other early prognostic biochemical biomarkers of EVA, CVDs (atherosclerosis and CAD) are being actively studied: neutrophil gelatinase-associated lipocalin (NGAL) [14]; tissue inhibitor of metalloproteinase 2 (TIMP-2) [14]; fibroblast growth factor 23 (FGF-23) [15,16]; syndecan-1 [16]; interleukin 6 (IL-6) [17]; and galectin-3 [18].
In addition, biomarkers of the adverse outcomes of atherosclerosis and CAD (total mortality and mortality from CVDs) are being developed, among which LTL is of undoubted scientific and clinical interest [19,20]. This is due to the fact that the mechanisms of LTL shortening in adults, which lead to stable CAD, acute coronary syndrome (ACS), and acute myocardial infarction (AMI), have not yet been sufficiently studied [21]. LTL is also actively studied in other CVDs (essential arterial hypertension [22,23], atrial fibrillation [24,25,26,27], cardiomyopathy [28], cerebrovascular diseases (stroke [29,30,31,32,33], vascular cognitive disorders [34,35], and vascular dementia [36]).
Telomeres (from the Greek telos “end” and meros “part”) are nucleoprotein structures located at the ends of chromosomes (Figure 1), consisting of a noncoding repetitive DNA sequence (-TTAGGG-), a single-stranded region called the protruding part of the G-chain [37,38], and proteins that compose the Shelterin complex. Due to the Shelterin proteins, telomeric DNA is folded into a complex three-dimensional structure [39,40]. The telomere length of an adult human is approximately 10–15 thousand base pairs (bp). The protruding part of the G-chain, including 150–200 bp, can bend and form a loop structure (T-loop). Also, a D-loop can be formed [39]. The T-loop protects the 3’OH ends of the chromosomes from recognition of 3’OH as a double break in the DNA chain [40,41].
Telomeres are bound to telomere-specific proteins that are part of the Shelterin complex. The Shelterin complex provides greater telomere stability and consists of six telomere-specific proteins: Telomeric Repeat Binding Factor 1 (TRF1); Telomeric Repeat Binding Factor 2 (TRF2); Telomeric Interacting Nuclear Factor 2 (TINF2 or TIN2), a complex consisting of TERF1 and Nuclear Factor 2; Protection of Telomeres 1 (POT1), a protein that provides telomere protection; Shelterin complex subunit and telomerase recruitment factor (TPP1), a subunit of Shelterin complex and telomerase recruitment factor; and TERF2 interacting protein (TERF2IP or RAP1), a protein that interacts with TERF2. All six proteins regulate telomere length [42].
The interaction of the Shelterin protein complex with the telomere DNA sequence ensures the stabilization of the telomere structure and regulates the access of proteins involved in DNA elongation and repair. The TRF1 complex is involved in telomere length control by regulating telomerase access to the telomere sequence [42]. The TRF2 complex protects the G-chain protrusion from degradation and prevents telomere fusion [43].
Telomeres were first identified by Hermann Müller in 1938 and he and McClintock determined the protective role of telomeres in 1941 [44]. The first human telomeres were isolated by Moyzic et al. [45] in 1988. Since then, telomere biology has been extensively studied.
Telomeres protect chromosome ends, maintaining genome integrity and stability [38]; telomeres prevent loss of coding DNA during DNA replication [39]. Chromosome telomere fusion can lead to gene amplification, chromosome imbalance, non-reciprocal translocations, and changes in gene expression [40,45]. Telomere length is shortened due to end replication problems and nucleolytic DNA degradation. Each cell division results in the loss of 50–200 bp of telomere sequence [40,46,47]. It is believed that telomere shortening is the reason for the limited number of divisions in most human cells. This phenomenon was first described by Hayflick [48] on diploid human cells. Also, he found that each cloned cell in the population is endowed with the same doubling potential—50 ± 10 cell divisions. This phenomenon was later called the “Hayflick Limit,” meaning that a cell can divide a limited number of times after which cell division stops [49].
In contrast to most somatic cells, hematopoietic stem cells, germ cells, keratinocytes in the basal layer of the epidermis, uterine endometrial cells, and cells from various tumors avoid telomere shortening by activating telomerase [40]. Telomerase, also called terminal transferase, is a ribonucleoprotein that adds a species-dependent telomere repeat sequence to the 3’ end of telomeres [50]. Although telomerase activity has been vigorously investigated over the last few decades, many questions remain open regarding the mechanisms of physiological regulation in normal cells [51]. The complex regulation at the levels of transcription, splicing, and post-transcriptional activation certainly contributes to that. Moreover, mutational analysis and knockdown experiments showed that telomerase deficiency led to telomere loss and uncapping, causing progressive atrophy of renewal tissues, a gradual depletion of stem cells, and the eventual failure of organ systems. Above all, telomerase may play a critical role in cellular and organismal aging and could be a potential target for anti-aging therapies [52].
Telomere shortening is associated with non-genetic (physiological) and genetic mechanisms of aging (inflammation, oxidative stress, chronic diseases, cellular aging, mortality), as well as with social factors of aging (gender, race, ethnicity, low socioeconomic status, stress, smoking) [47,53]. EVA syndrome, as well as age-associated diseases (CVDs, type 2 diabetes mellitus, cancer, or chronic obstructive pulmonary disease), are associated with telomere shortening and/or dysfunction [46]. For example, people with different degrees of atherosclerosis and CAD have significantly different LTL [52].
The purpose of this systematic review is to find, analyze, and systematize studies on the relationship between LTL and CAD.

2. Materials and Methods

Full-text publications were searched in the following databases: PubMed, Web of Science, Springer, Google Scholar, Oxford Press, Clinical Cases, Cochrane, and e-Library. We analyzed articles published between 10 January 2010 and 10 December 2021. Key words and their combinations were used to search for: “telomere length,” “stable coronary heart disease,” “humans,” “adults,” “coronary atherosclerosis,” “acute coronary syndrome,” “acute myocardial infarction,” “early vascular aging,” and “molecular predictors.”
Publications were searched and selected using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A total of 278 articles were found using the keywords (Figure 2). We analyzed original studies, systematic reviews and meta-analyses, clinical cases, and Cochrane reviews. After reading the relevant titles and abstracts, we excluded publications with irrelevant topics as well as duplicate publications, open access preprints, and conference posters. We excluded original studies that did not provide primary data, including demographic data, and original articles with retrospective studies. We also excluded reviews, editorials, animal experiments, and publications with questionable or insufficiently proven results of the authors’ investigated molecular biomarkers of CAD and the relationship between CAD and LTL. In addition, we analyzed earlier publications of historical interest.
Finally, we selected 14 suitable publications for our systematic review in which the authors used comparable methodological approaches to measure LTL using a T/S ratio and/or bp. This approach was important to be able to systematize the results of the analyzed studies. We analyzed but excluded from further processing publications with alternative methods of LTL calculation.
We selected articles in which the relative LTL was measured by the method of Cawthon R. M. [54]. This technique uses real-time quantitative polymerase chain reaction (PCR) to measure LTL. The advantages of this technique are speed of performance and a small amount of DNA. Relative LTL is defined as the ratio of telomeric repeats to a single copy of a standard gene (T/S) and is measured in conventional units (CU). The T/S ratio reflects the average LTL in all human leukocytes [55].
Statistical analysis of the obtained data was performed using the SPSS software package, version 23 (Stat Soft, Tulsa, AK, USA,). Since the size of compared samples was small (n ≤ 30), nonparametric statistics were used. Median (Me) and percentiles [25; 75] were calculated for each of the three groups (healthy adults without CVDs, adults with stable CAD, and adults with AMI). The groups were compared using the Mann–Whitney test. Significance of differences was considered significant at a p-value < 0.05.

3. Results

3.1. Leukocyte Telomere Length in Patients with Stable Coronary Heart Disease

Our analysis of the studies demonstrates that the issue of LTL changing in patients with CAD has been extensively studied worldwide. The number of LTL studies on this disease is increasing in different age groups of patients and in different racial and ethnic groups compared with healthy controls (Table 1). Thus, in healthy adults without CVD, the relative LTL ranged from 0.69 [56] to 1.52 CU [55] and the median relative LTL was 0.93 [0.70; 1.10] CU.
Hassler et al. [56] studied relative LTL in healthy adults (mean age of men 40.77 ± 11.62 years, mean age of women 44.71 ± 10.96 years). The authors found no significant difference in relative LTL in men and women of the study age (0.70 ± 0.28 vs. 0.69 ± 0.31 CU, p-value = 0.75).
In patients with stable CAD (Table 2), the relative LTL ranged from 0.82 [63] to 1.13 CU [55]; the median relative LTL was 0.86 [0.82; 1.07] CU. The differences in median LTL in patients with stable CAD compared to healthy controls were not statistically significant (p-value = 0.850).
Mazidi et al. [62] found that older men without CAD had a shorter relative LTL than younger men without CAD (6380 ± 80 bp vs. 12,420 ± 60 bp, p-value < 0.05).
Willeit et al. [55] in a prospective population-based PCR study, evaluated relative LTL in individuals aged 45 to 84 years without CVD and in patients with stable CAD. The authors found that LTL in patients with stable CAD was significantly shorter than in healthy individuals of the same age (1.13 ± 0.52 CU in patients with CAD versus 1.52 ± 0.81 CU in healthy individuals, p-value < 0.001). An interesting finding was that LTL was shorter in men than in women (1.41 [1.33–1.49] CU versus 1.55 [1.47–1.62] CU; p-value = 0.02). The authors attributed this phenomenon to the higher estrogen levels in women. In addition, the study found that LTL was inversely correlated with age (r = −0.22, p-value < 0.001).
The possibility of using LTL as a molecular biomarker of human biological aging as it reflects the telomere length of endothelial cells has been confirmed by several studies. The study of Hammadah et al. [63] established the relationship between LTL shortening and low level of CD34+ expression on human endothelial progenitor cells. After adjustment for age, sex, race, body mass index, smoking, and previous myocardial infarction, a shorter LTL was associated with lower CD34+ cell levels; for every 10% shorter relative LTL, CD34+ levels were 5.2% lower (p-value < 0.001). This is indirect evidence of the decreased regenerative capacity of bone marrow cells and the decreased repair of blood vessel endothelium. A study by Wilson et al. [66] revealed a strong correlation between endotheliocyte telomere length and relative LTL in the blood (r = 0.62, p-value < 0.001). Thus, LTL reflects vascular endotheliocyte telomere length, which allows us to use LTL assessment as a biomarker of vascular age, EVA, and human biological aging in various CVDs in adults.
Starnino et al. [61] found that patients with stable CAD had a shorter LTL compared with healthy volunteers and people without CVD (p-value < 0.001).
Tian et al. [58] analyzed cases of stable CAD in men younger than 55 years and women younger than 65 years. The authors measured relative LTL in Chinese patients with premature CAD compared with a control group (people of comparable age without CAD). The effects of oxidative stress on LTL shortening were assessed. Patients with premature CAD had a shorter relative LTL compared with those without CAD (0.88 ± 0.86 CU versus 1.1 ± 0.57 CU, p-value = 0.015). Thus, there was an association between LTL shortening and decreased plasma antioxidant capacity in patients with CAD.
Huang et al. [66] studied the relationship between LTL and all-cause mortality, cardiovascular mortality, and cerebrovascular mortality among adults in the USA. The study included 7827 participants (48.18% men). The researchers conventionally divided all participants by LTL into three groups: short LTL (0.77 ± 0.09 CU); medium relative LTL (1.00 ± 0.06 CU); and large LTL (1.32 ± 0.26 CU). After 158.26 months of follow-up, there were an average of 1876 (23.97%), 87 (1.11%), and 243 (3.10%) all-cause, cerebrovascular, and cardiovascular deaths. The authors showed that LTL was nonlinearly correlated with all-cause mortality (OR—95% CI: 0.03 to 0.09; p-value < 0.0001) but not with mortality from cerebrovascular disease and CVDs (p-value > 0.05).
Yakhontov et al. [64] studied the relationship between LTL in men with stable angina I-III functional classes according to the Canadian Cardiovascular Society classifications [67] in different age groups: the middle-aged group (median age 52 [46.5; 55] years) and the elderly group (median age 64 [62; 67] years). The authors found no statistically significant differences in LTL in patients with stable angina pectoris as a function of mean and old age (p-value = 0.058) [63]. Another study by these authors [64] examined LTL in young (median age 52 [46.5; 55] years) and middle-aged (median age 64 [62; 67] years) men with arterial hypertension and with stable angina I-III functional classes with and without EVA. The criteria for the inclusion of patients in the subgroup with EVA were a young age of arterial hypertension debut (before 45 years), a young age of CAD debut (before 45 years), and increased vascular wall stiffness according to the cardio-ankle vascular index (according to sonography). The authors showed that in men with arterial hypertension, CAD, and EVA, the relative LTL was statistically significantly shorter than in men with arterial hypertension and CAD but without EVA (p-value = 0.026) [65].
Thus, in recent years, researchers and clinicians have been very interested in studying the relationship between LTL and stable CAD. The number of ongoing studies is increasing. However, the results obtained vary over a wide range, which may be due to differences in patient age, ethnicity and race, and region of residence. Nevertheless, there is no doubt that LTL is reduced in middle-aged and elderly adults developing stable CAD compared with healthy adult controls without CVD including CAD [68].

3.2. Leukocyte Telomere Length in Patients with Acute Myocardial Infarction

The number of LTL studies in patients with AMI is still significantly lower compared to LTL studies in patients with stable CAD. We found and analyzed five studies (Table 3). In adults with AMI, the relative LTL ranged from 0.115 CU [60] to 0.86 CU [57]; the median relative LTL was 0.62 [0.20; 0.84] CU. Differences in mean LTL in patients with AMI compared with healthy controls were not statistically significant (p-value = 0.089).
Russo et al. [69] found no statistically significant association between relative LTL and the risk of AMI in an Italian cohort of younger patients (≤ 48 years).
However, Gupta et al. [60] demonstrated that the relative LTL adjusted for sex, age, and body mass index was statistically significantly greater in the control group (0.792 CU) compared with AMI patients (0.115 CU, p -value < 0.001).
Chan et al. [71] investigated LTL in 135 patients with ACS without ST elevations who underwent percutaneous coronary intervention. The mean age of the patients was 81 ± 4 years and 64% of them were men. The mean LTL was found to be 0.47 ± 0.25 CU. Then, patients were divided into 3 groups according to the relative LTL to assess the risk of adverse clinical outcomes (death, recurrent AMI, unplanned revascularization, stroke, significant bleeding) recorded 1 year from the time of the ASC diagnosis. Long LTL was taken as 0.74 ± 0.27 CU, medium LTL as 0.42 ± 0.05 CU, and short LTL as 0.25 ± 0.27 CU. The authors found no statistically significant association between relative LTL and adverse ACS outcomes in older Chinese people.
Dlouha et al. [57] found that the mean relative LTL in 505 elderly (mean age 61 ± 9.7 years) Czech women with AMI was statistically significantly lower than those in the control group (0.86 ± 0.32 CU vs. 0.93 ± 0.38 CU; p-value < 0.001). However, after adjusting for age, smoking status, and type 2 diabetes mellitus, the differences between the groups were no longer significant (p-value = 0.25). Thus, the authors concluded to the contrary that AMI was not associated with relative LTL in Czech women.
A study by Margaritis et al. [70] determined relative LTL in AMI patients in the United Kingdom. The results were presented as median and percentiles. Short LTL was considered to be less than 0.96 CU and long LTL ≥ 0.96 CU. The authors showed that LTL is a molecular biomarker of cardiovascular outcomes after AMI regardless of patients’ ages. Also, they demonstrated that short LTL (T/S < 0.916 CU) in patients with AMI is a predictor of the high risk of all-cause mortality (p-value = 0.008) and mortality from CVDs within the first year after AMI (p-value = 0.005).
Thus, in patients with AMI, the relative LTL ranged from 0.115 CU [60] to 0.86 CU [57].

4. Discussion

We found and analyzed a total of 17 publications including 5 studies conducted in Russia. However, three [72,73,74] of the five Russian studies were excluded from the subsequent systematic analysis due to an alternative methodological approach to LTL measurement. The results of the 14 publications were systematized and ranked into 3 groups (adults without CVDs, adults with stable CAD, and adults with AMI), as demonstrated in Table 1, Table 2 and Table 3.
We demonstrated that in studies of the mean relative LTL in young, middle-aged, and elderly adults, the value of this molecular biomarker decreases not only in relation to the physiological biological aging of the human body but also in relation to the premature development of stable CAD [64] and the early development of AMI [60]. At the same time, the most convincing results were obtained in studies of relative LTL in middle-aged and elderly patients with stable CAD [55,58,59,61,63,64,65]. It seems important from a practical point of view because patients with stable CAD and with shortened relative LTL can have unfavorable prognoses concerning general mortality [75]. However, the prognosis of cardiovascular and cerebrovascular mortality in patients with stable CAD and with shortened LTL need to be clarified in the future.
Interestingly, the relative LTL in patients with AMI (Table 3) is shorter compared with the relative LTL in patients with CAD (Table 2) and with healthy controls (Table 1). However, we must admit that the small number of studies of relative LTL in patients with AMI does not allow us to draw any definitive conclusions.
Studies of relative LTL in patients with AMI (predominantly) and with stable CAD (to a lesser extent) are in their infancy. Such studies are still in the minority, the sample sizes are small, and the results obtained in some studies are contradictory [60,69,70,71]. The ethnic and racial heterogeneity of the samples in the publications we analyzed draws attention, which does not allow us to assess the additional influences of ethnicity and region of residence of adults with and without the studied CVDs on the absolute and relative LTL.
However, our systematic review of available publications demonstrated a trend toward shorter relative LTL in patients with AMI (0.62 [0.20; 0.84] CU) compared with patients with stable CAD (0.86 [0.82; 1.07] CU) and a healthy control group (0.93 [0.70; 1.10] CU) (Figure 3). However, these results did not reach statistical significance (p-value > 0.05). Nevertheless, this trend could be clarified by new, large, and multicenter studies with a similar design in the future.
Thus, CAD and arterial hypertension [76,77,78,79,80,81], CAD and atrial fibrillation [82,83,84,85,86,87,88,89,90,91] and CAD and vascular cognitive disorders [92,93,94,95] are common comorbid conditions with overlap syndrome. Therefore, the study of LTL seems important not only in isolated CAD and AMI but also in these syndromes of mutual aggravation.

5. Limitations

The limitations of this systematic review include the analysis of publications in English and Russian only. It is possible that we missed some studies published in other languages that were not represented in the databases we analyzed.
Another limitation of the review of published and available studies of relative LTL in adults with CVDs is the different methodological approaches of the investigators with regard to the study design, inclusion/exclusion criteria (e.g., age and sex of patients, ethnic group, etc.), and study duration (most studies were cross-sectional, not longitudinal). In addition, some authors used % rather than CU to estimate relative LTL.
Due to methodological problems (differences in how LTL is calculated), three Russian-language publications were excluded from the review. Thus, an interesting study is by Maximov et al. [72], in which the association of LTL with various risk factors of age-associated diseases in the Russian population was studied. The authors identified a group of patients with stable CAD in whom LTL was determined, but no recalculation of mean age and percentage by gender was performed for this group of patients, which did not allow us to include this study in our systematic review. Strajesko et al. [73] studied the relationship between risk factors for CVDs and LTL, but the authors used an alternative approach to LTL measurement, unlike the methods in the English-language publications we analyzed. Thus, the authors took 9.75 units as a short LTL and more than or equal to 9.75 units as a long LTL. Thus, the approach to determining the relative LTL in the English-language and some Russian-language publications differed significantly. In addition, the authors used three models based on multivariate linear regression analysis [73] to assess the relationship between LTL and CVD risk factors, which is of undoubted scientific interest. However, this method of statistical analysis was not used in other publications we analyzed. The authors showed that relative LTL was associated with the mean and old age of the individuals included in the study, but this publication lacked baseline data on LTL in patients with stable CAD and healthy adults. This limitation prevented us from including the authors’ findings in our systematic review. Doroshchuk et al. [74] used LTL in patients with stable CAD compared to a group of age-matched healthy volunteers as the study index. The authors demonstrated that LTL statistically significantly decreased with increasing cardiovascular mortality risk according to the Systematic Coronary Risk Evaluation (SCORE) scale, p-value < 0.005. However, the authors used an alternative method of measuring LTL—not in CU, but as a percentage compared to healthy controls. Due to the alternative LTL calculation methodology, the results of this study were also not included in our systematic review.
The other main concern is that relative measured LTL cannot be compared between studies, but relative measured LTLs are comparable between groups inside one study. This is due to the fact that relative LTL measured as the T/S ratio measures the relative amount of telomeric DNA (T) to a single copy gene (S), calibrated to a plate reference genomic DNA sample. Therefore, and as this reference sample is unique for each study, the results on relative quantified LTLs are not directly comparable between studies.
The association between LTL and EVA has had a limited focus in the present review and we therefore plan to include it in a future review of the relationship between EVA and LTL in young, middle-aged, and elderly patients.

6. Conclusions

Despite the scientific and clinical significance of the analyzed studies on relative LTL as a molecular biomarker of CVDs, their translation into real clinical practice is difficult due to disparities in the design and methodology of the analyzed studies, including the studies on cell cultures and humans, as well as the differences in samples by gender, age, race, and ethnicity. The authors believe that clinical studies of the role of relative LTL in adult patients with CAD are the most promising and require large multicenter studies with a unified design and methodology.

Author Contributions

Conceptualization, N.A.S.; methodology, O.V.Z. and N.A.S.; software, O.V.Z.; validation, O.V.Z. and M.A.-Z.; formal analysis, O.V.Z. and N.A.S.; investigation, O.V.Z. and M.S.C.; resources, O.V.Z. and N.V.L.; data curation, O.V.Z., M.M.P. and M.A.-Z.; writing—original draft preparation, O.V.Z., N.A.S. and A.E.I.; writing—review and editing, N.A.S. & M.M.P.; visualization, O.V.Z. and N.A.S.; supervision, N.A.S.; project administration, M.M.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors thank Ekaterina V. Kachura ([email protected]) for help in preparing the figures.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Timmis, A.; Townsend, N.; Gale, C.P.; Torbica, A.; Lettino, M.; Petersen, S.E.; Mossialos, E.A.; Maggioni, A.P.; Kazakiewicz, D.; May, H.T.; et al. European Society of Cardiology: Cardiovascular Disease Statistics 2019. Eur. Heart J. 2020, 41, 12–85. [Google Scholar] [CrossRef] [PubMed]
  2. Shalnova, S.A.; Drapkina, O.M. The trends of cardiovascular and cancer mortality in Russian men and women from 2000 to 2016 years. Ration. Pharmacother. Cardiol. 2019, 15, 77–83. [Google Scholar] [CrossRef]
  3. Ageeva, L.I.; Alexandrova, G.A.; Golubev, N.A.; Kirillova, G.N.; Ogryzko, E.V.; Oskov, Y.I.; Nam, P.D.; Kharkov, T.L.; Chumarina, V.Z. Healthcare in Russia. 2021: Stat.sat./Rosstat.—M., 2021, 171 p. Available online: https://ghdx.healthdata.org/organizations/federal-state-statistics-service-russia (accessed on 1 June 2022).
  4. Kolber, M.R.; Scrimshaw, C. Family history of cardiovascular disease. Can. Fam Physician 2014, 60, 1016. [Google Scholar] [PubMed]
  5. Hamczyk, M.R.; Nevado, R.M.; Barettino, A.; Fuster, V.; Andres, V. Biological versus chronological aging: JACC focus seminar. J. Am. Coll. Cardiol. 2020, 75, 919–930. [Google Scholar] [CrossRef]
  6. Nilsson, P.M. Early vascular aging (EVA): Consequences and prevention. Vasc. Health Risk Manag. 2008, 4, 547–552. [Google Scholar] [CrossRef] [Green Version]
  7. Thijssen, D.H.J.; Bruno, R.M.; Mil, A.C.C.M.; Holder, S.M.; Faita, F.; Greyling, A.; Zock, P.L.; Taddei, S.; Deanfield, J.E.; Luscher, T.; et al. Expert consensus and evidence-based recommendations for the assessment of flow mediated dilation in humans. Eur. Heart J. 2019, 40, 2534–2547. [Google Scholar] [CrossRef]
  8. Bauer, M.; Caviezel, S.; Teynor, A.; Erbel, R.; Mahabadi, A.A.; Schmidt-Trucksass, A. Carotid intima-media thickness as a bio-marker of subclinical atherosclerosis. Swiss Med. Wkly. 2012, 142, w13705. [Google Scholar] [CrossRef]
  9. Grillo, A.; Lonati, A.M.; Guida, V.; Parati, G. Cardio-ankle vascular stiffness index (CAVI) and 24-h blood pressure profiles. Eur. Heart J. Suppl. 2017, 19 (Suppl. B), 17–23. [Google Scholar] [CrossRef]
  10. Townsend, R.R.; Wilkinson, I.B.; Schiffrin, E.L.; Townsend, R.R.; Wilkinson, I.B.; Schiffrin, E.L.; Avolio, A.P.; Chirinos, J.A.; Cockcroft, J.R.; Heffernan, K.S.; et al. Recommendations for improving and standardizing vascular research on arterial stiffness: A scientific statement from the American Heart Association. Hypertension 2015, 66, 698–722. [Google Scholar] [CrossRef] [Green Version]
  11. Lanzer, P.; Boehm, M.; Sorribas, V.; Thiriet, M.; Janzen, J.; Zeller, T.; Hilaire, C.S.; Shanahan, C. Medial vascular calcification revisited: Review and perspectives. Eur. Heart J. 2014, 35, 1515–1525. [Google Scholar] [CrossRef]
  12. De Meyer, T.; Nawrot, T.; Bekaert, S.; De Buyzere, M.L.; Rietzschel, E.R.; Andres, V. Telomere length as cardiovascular aging biomarker: JACC review topic of the week. J. Am. Coll. Cardiol. 2018, 72, 805–813. [Google Scholar] [CrossRef] [PubMed]
  13. Burko, N.V.; Avdeeva, I.V.; Oleynikov, V.E.; Boytsov, S.A. The concept of early vascular aging. Ration. Pharmacother. Cardiol. 2019, 15, 742–749. [Google Scholar] [CrossRef] [Green Version]
  14. Marco, L.D.; Bellasi, A.; Raggi, P. Cardiovascular biomarkers in chronic kidney disease: State of current research and clinical applicability. Dis. Markers 2015, 586569. [Google Scholar] [CrossRef] [Green Version]
  15. Gregoli, K.D.; George, S.J.; Jackson, C.L.; Newby, A.C.; Johnson, J.L. Differential effects of tissue inhibitor of metalloproteinase (TIMP)-1 and TIMP-2 on atherosclerosis and monocyte/macrophage invasion. Cardiovasc. Res. 2016, 109, 318–330. [Google Scholar] [CrossRef]
  16. Freitas, I.A.; Lima, N.A.; Silva, G.B.; Castro, R.L.; Patel, P.; Vasconcelos Lima, C.C.; Costa Lino, D.O. Novel biomarkers in the prognosis of patients with atherosclerotic coronary artery disease. Port. J. Cardiol. 2020, 39, 667–672. [Google Scholar] [CrossRef]
  17. Wainstein, M.V.; Mossmann, M.; Araujo, G.N.; Gonçalves, S.C.; Gravina, G.L.; Sangalli, M.; Veadrigo, F.; Matte, R.; Reich, R.; Costa, F.G.; et al. Elevated serum interleukin-6 is predictive of coronary artery disease in intermediate risk over-weight patients referred for coronary angiography. Diabetol. Metab. Syndr. 2017, 9, 67. [Google Scholar] [CrossRef]
  18. Velde, A.R.; Lexis, C.P.H.; Meijers, W.C.; Horst, I.C.; Lipsic, E.; Dokter, M.M.; Veldhuisen, D.J.; Harst, P.; Boer, R.A. Galectin-3 and sST2 in prediction of left ventricular ejection fraction after myocardial infarction. Clin. Chim. Acta 2016, 452, 50–57. [Google Scholar] [CrossRef] [PubMed]
  19. Sun, Y.; Zhao, J.Q.; Jiao, Y.R.; Ren, J.; Zhou, Y.H.; Li, L.; Yao, H.C. Predictive value of leukocyte telomere length for the severity of coronary artery disease. Pers. Med. 2020, 17, 175–183. [Google Scholar] [CrossRef]
  20. Sun, Y.; Wang, W.; Jiao, Y.R.; Ren, J.; Gao, L.; Li, Y.; Hu, P.; Ren, T.Y.; Han, Q.F.; Chen, C.; et al. Leukocyte telomere length: A potential biomarker for the prognosis of coronary artery disease. Biomark. Med. 2020, 14, 933–941. [Google Scholar] [CrossRef]
  21. Xu, X.; Hu, H.; Lin, Y.; Huang, F.; Ji, H.; Li, Y.; Lin, S.; Chen, X.; Duan, S. Differences in leukocyte telomere length between coronary heart disease and normal population: A Multipopulation Meta-Analysis. BioMed Res. Int. 2019, 5046867. [Google Scholar] [CrossRef]
  22. Ma, L.N.; Li, Y.; Wang, J.Y. Telomeres, and essential hypertension. Clin. Biochem. 2015, 48, 1195–1199. [Google Scholar] [CrossRef] [PubMed]
  23. Cheng, G.; Wang, L.; Dai, M.; Wei, F.; Xu, D. Shorter leukocyte telomere length coupled with lower expression of telomerase genes in patients with essential hypertension. Int. J. Med. Sci. 2020, 17, 2180–2186. [Google Scholar] [CrossRef]
  24. Allende, M.; Molina, E.; González-Porras, J.R.; Toledo, E.; Lecumberri, R.; Hermida, J. Short leukocyte telomere length is associated with cardioembolic stroke risk in patients with atrial fibrillation. Stroke 2016, 47, 863–865. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Wang, S.; Gao, Y.; Zhao, L.; Hu, R.; Yang, X.; Liu, Y. Shortened leukocyte telomere length as a potential biomarker for predicting the progression of atrial fibrillation from paroxysm to persistence in the short-term. Medicine 2021, 100, e26020. [Google Scholar] [CrossRef] [PubMed]
  26. Hayashi, T. Vascular senescense and endothelial function—Can we apply it to atrial fibrillation? Circ. J. 2019, 83, 1439–1440. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Nikulina, S.I.; Shishkova, K.I.; Shulman, V.A.; Chernova, A.A.; Maksimov, V.N. Peripheral blood leukocyte telomere length as a possible prognostic marker for the development of atrial fibrillation. CardioSomatics 2020, 11, 50–54. [Google Scholar] [CrossRef]
  28. Chatterjee, S.; Gonzalo-Calvo, D.; Derda, A.A.; Schimmel, K.; Sonnenschein, K.; Bavendiek, U.; Bauersachs, J.; Bar, C.; Thum, T. Leukocyte telomere length correlates with hypertrophic cardiomyopathy severity. Sci. Rep. 2018, 8, 11227. [Google Scholar] [CrossRef]
  29. Wang, Y.; Jiao, F.; Zheng, H.; Kong, Q.; Li, R.; Zhang, X.; Yan, L.; Hao, Y.; Wu, Y. Gender difference in associations between telomere length and risk factors in patients with stroke. Front. Aging Neurosci. 2021, 13, 719538. [Google Scholar] [CrossRef]
  30. Yetim, E.; Topcuoglu, M.A.; Kutlay, N.Y.; Tukun, A.; Oguz, K.K.; Arsava, E.M. The association between telomere length and ischemic stroke risk and phenotype. Sci. Rep. 2021, 11, 10967. [Google Scholar] [CrossRef]
  31. Cao, W.; Zheng, D.; Zhang, J.; Wang, A.; Liu, D.; Zhang, J.; Singh, M.; Maranga, I.E.; Cao, M.; Wu, L.; et al. Association between telomere length in peripheral blood leukocytes and risk of ischemic stroke in a Han Chinese population: A linear and non-linear Mendelian randomization analysis. J. Transl. Med. 2020, 18, 385. [Google Scholar] [CrossRef]
  32. Tian, Y.J.; Wang, S.; Jiao, F.J.; Kong, Q.; Liu, C.; Wu, Y. Telomere length: A potential biomarker for the risk and prognosis of stroke. Front. Neurol. 2019, 10, 624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Li, J.; Feng, C.; Li, L.; Yang, S.; Chen, Y.; Hui, R.; Zhang, M.; Zhang, W. The association of telomere attrition with first-onset stroke in Southern Chinese: A case-control study and meta-analysis. Sci. Rep. 2018, 8, 2290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Yu, J.; Kanchi, M.M.; Rawtaer, I.; Feng, L.; Kumar, A.P.; Kua, E.H.; Mahendran, R. The functional and structural connectomes of telomere length and their association with cognition in mild cognitive impairment. Cortex 2020, 132, 29–40. [Google Scholar] [CrossRef] [PubMed]
  35. Yang, T.; Wang, H.; Xiong, Y.; Chen, C.; Duan, K.; Jia, J.; Ma, F. Vitamin D supplementation improves cognitive function through reducing oxidative stress regulated by telomere length in older adults with mild cognitive impairment: A 12-month randomized controlled trial. J. Alzheimers Dis. 2020, 78, 1509–1518. [Google Scholar] [CrossRef]
  36. Hinterberger, M.; Fischer, P.; Huber, K.; Krugluger, W.; Zehetmayer, S. Leukocyte telomere length is linked to vascular risk factors not to Alzheimer’s disease in the VITA study. J. Neural Transm. 2017, 124, 809–819. [Google Scholar] [CrossRef]
  37. Blackburn, E.H.; Appel, E.S.; Link, J. Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection. Science 2015, 350, 1193–1198. [Google Scholar] [CrossRef] [Green Version]
  38. Yeh, J.K.; Wang, C.Y. Telomeres and telomerase in cardiovascular diseases. Genes 2016, 7, 58. [Google Scholar] [CrossRef] [Green Version]
  39. Herrmann, M.; Pusceddu, I.; Marz, W.; Herrmann, W. Telomere biology and age-related diseases. Clin. Chem. Labor-Atory Med. 2018, 56, 1210–1222. [Google Scholar] [CrossRef]
  40. Pusceddu, I.; Farrell, C.J.L.; Di Pierro, A.M.; Jani, E.; Herrmann, W.; Herrmann, M. The role of telomeres and vitamin D in cellular aging and age-related diseases. Clin. Chem. Lab. Med. 2015, 53, 1661–1678. [Google Scholar] [CrossRef] [Green Version]
  41. Dorajoo, R.; Chang, X.; Gurung, R.L.; Li, Z.; Wang, L.; Wang, R.; Beckman, K.B.; Adams-Haduch, J.; M, Y.; Liu, S.; et al. Loci for human leukocyte telomere length in the Singaporean Chinese population and trans-ethnic genetic studies. Nat. Commun. 2019, 10, 2491. [Google Scholar] [CrossRef] [Green Version]
  42. Turner, K.J.; Vasu, V.; Darren, K.; Griffin, D.K. Telomere biology and human phenotype. Cells 2019, 8, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Salakhov, R.R.; Ponasenko, A.V. Telomere length and cardiovascular diseases. Complex. Issues Cardiovasc. Dis. 2018, 7, 101–107. [Google Scholar] [CrossRef]
  44. McClintock, B. The stability of broken ends of chromosomes in zea mays. Genetics 1941, 26, 234–282. [Google Scholar] [CrossRef] [PubMed]
  45. Moyzis, R.K.; Buckingham, J.M.; Cram, L.S.; Dani, M.; Deaven, L.L.; Jones, M.D.; Meyne, J.; Ratliff, R.L.; Wu, J.R. A highly con-served repetitive DNA sequence, (TTAGGG)n, present at the telomeres of human chromosomes. Proc. Natl. Acad. Sci. USA 1988, 85, 6622–6666. [Google Scholar] [CrossRef] [Green Version]
  46. Armanios, M. Telomeres and age-related disease: How telomere biology informs clinical paradigms. J. Clin. Investig. 2013, 123, 996–1002. [Google Scholar] [CrossRef] [Green Version]
  47. Brown, L.L.; Zhang, Y.S.; Mitchell, C.; Ailshire, J. Does telomere length indicate biological, physical, and cognitive health among older adults? Evidence from the Health and Retirement Study. J. Gerontol. 2018, 73, 1626–1632. [Google Scholar] [CrossRef] [Green Version]
  48. Hayflick, L. The limited in vitro lifetime of human diploid cell strains. Exp. Cell Res. 1965, 37, 614–636. [Google Scholar] [CrossRef]
  49. Samani, N.J.; Boultby, R.; Butler, R.; Thompson, J.R.; Goodall, A.H. Telomere shortening in atherosclerosis. Lancet 2001, 358, 472–473. [Google Scholar] [CrossRef]
  50. Rubtsova, M.; Dontsova, O. Human telomerase RNA: Telomerase component or more? Biomolecules 2020, 10, 873. [Google Scholar] [CrossRef]
  51. Arai, Y.; Martin-Ruiz, C.M.; Takayama, M.; Abe, Y.; Takebayashi, T.; Koyasu, S.; Suematsu, M.; Hirose, N.; von Zglinicki, T. Inflammation, but not telomere length, predicts successful ageing at extreme old age: A longitudinal study of semi-supercentenarians. EBioMedicine 2015, 2, 1549–1558. [Google Scholar] [CrossRef] [Green Version]
  52. Allsopp, R.C.; Morin, G.B.; DePinho, R.; Harley, C.B.; Weissman, I.L. Telomerase is required to slow telomere shortening and extend replicative lifespan of HSCs during serial transplantation. Blood 2003, 102, 517–520. [Google Scholar] [CrossRef] [Green Version]
  53. Bhattacharyya, J.; Mihara, K.; Bhattacharjee, D.; Mukherjee, M. Telomere length as a potential biomarker of coronary artery disease. Indian J. Med. Res. 2017, 145, 730–737. [Google Scholar] [CrossRef] [PubMed]
  54. Cawthon, R.M. Telomere measurement by quantitative PCR. Nucleic Acids Res. 2002, 30, e47. [Google Scholar] [CrossRef] [PubMed]
  55. Willeit, P.; Willeit, J.; Brandstätter, A.; Ehrlenbach, S.; Mayr, A.; Gasperi, A.; Weger, S.; Oberhollenzer, F.; Reindl, M.; Kronenberg, F.; et al. Cellular aging reflected by leukocyte telomere length predicts advanced atherosclerosis and cardiovascular disease risk. Arterioscler. Thromb. Vasc. Biol. 2010, 30, 1649–1656. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Hassler, E.; Almer, G.; Reishofer, G.; Marsche, G.; Mangge, H.; Deutschmann, H.; Herrmann, M.; Leber, S.; Gunzer, F.; Renner, W. Sex-specific association of serum antioxidative capacity and leukocyte telomere length. Antioxidants 2021, 10, 1908. [Google Scholar] [CrossRef]
  57. Dlouha, D.; Pitha, J.; Mesanyova, J.; Mrazkova, J.; Fellnerova, A.; Stanek, V.; Lanska, V.; Hubacek, J.A. Genetic variants within telomere-associated genes, leukocyte telomere length and the risk of acute coronary syndrome in Czech women. Clin. Chim. Acta 2016, 454, 62–65. [Google Scholar] [CrossRef]
  58. Tian, R.; Zhang, L.N.; Zhang, T.T.; Pang, H.Y.; Chen, L.F.; Shen, Z.J.; Liu, Z.; Fang, Q.; Zhang, S.Y. Association between oxidative stress and peripheral leukocyte telomere length in patients with premature coronary artery disease. Med. Sci. Monit. 2017, 23, 4382–4390. [Google Scholar] [CrossRef] [Green Version]
  59. Pejenaute, A.; Cortes, A.; Marques, J.; Montero, L.; Beloqui, O.; Fortuno, A.; Martí, A.; Orbe, J.; Zalba, G. NADPH oxidase overactivity underlies telomere shortening in human atherosclerosis. Int. J. Mol. Sci. 2020, 21, 1434. [Google Scholar] [CrossRef] [Green Version]
  60. Gupta, M.D.; Miglani, M.; Bansal, A.; Jain, V.; Arora, S.; Kumar, S.; Virani, S.S.; Kalra, A.; Yadav, R.; Pasha, Q.; et al. Telomere length in young patients with acute myocardial infarction without conventional risk factors: A pilot study from a South Asian population. Indian Heart J. 2020, 72, 619–622. [Google Scholar] [CrossRef]
  61. Starnino, L.; Dupuis, G.; Busque, L.; Bourgoin, V.; Dube, M.P.; Busseuil, D.; D’Antono, B. The associations of hostility and defensiveness with telomere length are influenced by sex and health status. Biol. Sex. Differ. 2021, 12, 2. [Google Scholar] [CrossRef]
  62. Mazidi, M.; Shekoohi, N.; Katsiki, N.; Rakowski, M.; Mikhailidis, D.P.; Banach, M. Serum anti-inflammatory and inflammatory markers have no causal impact on telomere length: A Mendelian randomization study. Arch. Med. Sci. 2021, 17, 739–751. [Google Scholar] [CrossRef] [PubMed]
  63. Hammadah, M.; Mheid, I.A.; Wilmot, K.; Ramadan, R.; Abdelhadi, N.; Alkhoder, A.; Obideen, M.; Pimple, P.M.; Levantsevych, O.; Kelli, H.M.; et al. Telomere shortening, regenerative capacity, and cardiovascular outcomes. Circ. Res. 2017, 120, 1130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Yakhontov, D.A.; Ostanina, J.O.; Pakharukova, M.Y.; Mordvinov, V.A. Clinical sings and symptoms of polyvascular disease in coronary artery disease patients of different age groups. Complex. Issues Cardiovasc. Dis. 2017, 6, 36–43. [Google Scholar] [CrossRef] [Green Version]
  65. Yakhontov, D.A.; Ostanina, J.O. Early vascular aging syndrome in young and middle age patients with hypertension and coronary artery disease. Med. Alph. 2018, 1, 33–36. [Google Scholar]
  66. Wilson, R.W.; Herbert, K.E.; Mistry, Y.; Stevens, S.E.; Patel, H.R.; Hastings, R.A.; Thompson, M.M.; Williams, B. Blood leukocyte telomere DNA content predicts vascular telomere DNA content in humans with and without vascular disease. Eur. Heart J. 2008, 29, 2689–2694. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Huang, Y.Q.; Lo, K.; Feng, Y.Q.; Zhang, B. The association of mean telomere length with all-cause, cerebrovascular and cardiovascular mortality. Biosci. Rep. 2019, 39, BSR20192306. [Google Scholar] [CrossRef] [Green Version]
  68. Clinical Recommendations. Stable Coronary Heart Disease. Russian Society of Cardiology 2020.—Text: Electronic. Available online: https://scardio.ru/content/Guidelines/2020/Clinic_rekom_IBS.pdf (accessed on 20 November 2021).
  69. Russo, A.; Palumbo, L.; Fornengo, C. Telomere length variation in juvenile acute myocardial infarction. PLoS ONE 2012, 7, e49206. [Google Scholar] [CrossRef] [PubMed]
  70. Margaritis, M.; Sanna, F.; Lazaros, G.; Akoumianakis, I.; Patel, S.; Antonopoulos, A.S.; Duke, C.; Herdman, L.; Psarros, C.; Oikonomou, E.K.; et al. Predictive value of telomere length on outcome following acute myocardial infarction: Evidence for contrasting effects of vascular vs. blood oxidative stress. Eur. Heart J. 2017, 38, 3094–3104. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Chan, D.; Martin-Ruiz, C.; Saretzki, G.; Neely, D.; Qiu, W.; Kunadian, V. The association of telomere length and telomerase activity with adverse outcomes in older patients with non-ST-elevation acute coronary syndrome. PLoS ONE 2020, 15, e0227616. [Google Scholar] [CrossRef] [PubMed]
  72. Maximov, V.N.; Malyutina, S.K.; Orlov, P.S.; Ivanoschuk, D.E.; Voropaeva, E.N.; Bobak, M.; Voevoda, M.I. Length telomere leukocytes as aging markers and risk factors for age-related disease in humans. Adv. Gerontol. 2016, 29, 702–708. [Google Scholar] [CrossRef]
  73. Strajesko, I.D.; Tkacheva, I.N.; Akasheva, D.U.; Dudinskaya, E.V.; Agaltsov, M.V.; Kruglikova, A.S.; Brailova, N.V.; Pykhtina, V.S.; Plokhova, E.V.; Ozerova, I.N.; et al. Relation of cardiovascular risk factors and leukocyte telomere length. Cardiovasc. Ther. Prev. 2016, 15, 52–57. [Google Scholar] [CrossRef] [Green Version]
  74. Doroshchuk, N.A.; Tikhase, A.K.; Lankin, V.Z.; Konovalova, G.G.; Mednikova, T.K.; Postnov, A.Y.; Kukharchuk, V.V. The influence of oxidative stress on the length of telomeric repeats in chromosomes o white blood cells in patients with coronary artery disease. Cardiol. Bull. 2017, 12, 32–37. [Google Scholar]
  75. Wang, H.; Naghavi, M.; Allen, C.; Barber, R.M.; Bhutta, Z.B.; Carter, A.; Casey, D.C.; Charlson, F.J.; Chen, A.Z.; Coates, M.M.; et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: A systematic analysis for the Global Burden of Disease Study 2015. The Lancet. 2016, 388, 1459–1544. [Google Scholar] [CrossRef] [Green Version]
  76. Oganov, R.G.; Simanenkov, V.I.; Bakulin, I.G.; Bakulina, N.V.; Barbarash, O.L.; Boytsov, S.A.; Boldueva, S.A.; Garganeeva, N.P.; Doshchitsin, V.L.; Karateev, A.E.; et al. Comorbidities in clinical practice. Algorithms for diagnostics and treatment. Cardiovasc. Ther. Prevention. 2019, 18, 5–66. [Google Scholar] [CrossRef]
  77. Paluch, W.; Semczuk, K.; Rys, A.; Szymanski, F.M.; Filipiak, K.J. Anti-hypertensive treatment efficacy in patients with arterial hypertension and coronary artery disease or coronary equivalent. Arter. Hypertens. 2017, 21, 93–98. [Google Scholar] [CrossRef] [Green Version]
  78. Zhang, W.Y.; Zhang, J.; Jin, F.; Zhou, H. Efficacy of felodipine and enalapril in the treatment of essential hypertension with coronary artery disease and the effect on levels of salusin-β, apelin, and PON1 gene expression in patients. Cell. Mol. Biol. 2021, 67, 174–180. [Google Scholar] [CrossRef]
  79. Sarkar, G.; Gaikwad, V.B.; Sharma, A.; Halder, S.K.; Kumar, D.A.; Anand, J.; Agrawal, S.; Kumbhar, A.; Kinholkar, B.; Mathur, R.; et al. Fixed-dose combination of metoprolol, telmisartan, and chlorthalidone for essential hypertension in adults with stable coronary artery disease: Phase III Study. Adv. Ther. 2022, 39, 923–942. [Google Scholar] [CrossRef]
  80. Zheng, Y.; Li, D.; Zeng, N.; Guo, H.; Li, H.; Shen, S. Trends of antihypertensive agents in patients with hypertension and coronary artery disease in a tertiary hospital of China. Int. J. Clin. Pharmacol. Ther. 2020, 42, 482–488. [Google Scholar] [CrossRef]
  81. Guo, Q.; Lu, X.; Gao, Y.; Zhang, J.; Yan, B.; Su, D.; Song, A.; Zhao, X.; Wang, G. Cluster analysis: A new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients. Sci. Rep. 2017, 7, 43965. [Google Scholar] [CrossRef] [Green Version]
  82. Steensig, K.; Olesen, K.K.W.; Thim, T.; Nielsen, J.C.; Jensen, S.E.; Jensen, L.O.; Kristensen, S.D.; Botker, H.E.; Lip, G.Y.H.; Maeng, M. CAD is an independent risk factor for stroke among patients with atrial fibrillation. J. Am. Coll. Cardiol. 2018, 72, 2540–2542. [Google Scholar] [CrossRef]
  83. Michniewicz, E.; Mlodawska, E.; Lopatowska, P.; Tomaszuk-Kazberuk, A.; Malyszko, J. Patients with atrial fibrillation and coronary artery disease—Double trouble. Adv. Med. Sci. 2018, 63, 30–35. [Google Scholar] [CrossRef] [PubMed]
  84. Gladding, P.A.; Legget, M.; Fatkin, D.; Larsen, P.; Doughty, R. Polygenic risk scores in coronary artery disease and atrial fibrillation. Heart Lung Circ. 2020, 29, 634–640. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  85. Alkindi, F.A.; Rafie, I.M. Anticoagulation in patients with atrial fibrillation and coronary artery disease. Heart Views 2020, 21, 32–36. [Google Scholar] [CrossRef] [PubMed]
  86. Nortamo, S.; Kentta, T.V.; Ukkola, O.; Huikuri, H.V.; Perkiomaki, J.S. Supraventricular premature beats and risk of new-onset atrial fibrillation in coronary artery disease. J. Cardiovasc. Electrophysiol. 2017, 28, 1269–1274. [Google Scholar] [CrossRef]
  87. Zheng, Y.J.; He, J.Q. Common differentially expressed genes and pathways correlating both coronary artery disease and atrial fibrillation. Excli J. 2021, 20, 126–141. [Google Scholar] [CrossRef] [PubMed]
  88. Pastori, D.; Pignatelli, P.; Sciacqua, A.; Perticone, M.; Violi, F.; Lip, G.Y.H. Relationship of peripheral and coronary artery disease to cardiovascular events in patients with atrial fibrillation. Int. J. Cardiol. 2018, 255, 69–73. [Google Scholar] [CrossRef]
  89. Inohara, T.; Shrader, P.; Pieper, K.; Blanco, R.G.; Allen, L.A.; Fonarow, G.C.; Gersh, B.J.; Go, A.S.; Ezekowitz, M.D.; Kowey, P.R.; et al. Treatment of atrial fibrillation with concomitant coronary or peripheral artery disease: Results from the outcomes registry for better informed treatment of atrial fibrillation II. Am. Heart J. 2019, 213, 81–90. [Google Scholar] [CrossRef]
  90. Lamblin, N.; Ninni, S.; Tricot, O.; Meurice, T.; Lemesle, G.; Bauters, C. Secondary prevention and outcomes in outpatients with coronary artery disease, atrial fibrillation or heart failure: A focus on disease overlap. Open Heart 2020, 7, e001165. [Google Scholar] [CrossRef] [Green Version]
  91. Wakili, R.; Riesinger, L.; Fender, A.C.; Dobrev, D. Double Jeopardy: Will the new trials tell us how to manage patients with atrial fibrillation and coronary artery disease? IJC Heart Vasc. 2019, 23, 100369. [Google Scholar] [CrossRef]
  92. Suridjan, I.; Herrmann, N.; Adibfar, A.; Saleem, M.; Andreazza, A.; Oh, P.I.; Lanctot, K.L. Lipid peroxidation markers in coronary artery disease patients with possible vascular mild cognitive impairment. J. Alzheimer’s Dis. 2017, 58, 885–896. [Google Scholar] [CrossRef] [Green Version]
  93. Xia, C.; Vonder, M.; Sidorenkov, G.; Oudkerk, M.; de Groot, J.C.; Harst, P.; Bock, G.H.; De Deyn, P.P.; Vliegenthart, R. The relationship of coronary artery calcium and clinical coronary artery disease with cognitive function: A systematic review and meta-analysis. J. Atheroscler. Thromb. 2020, 27, 934–958. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Saleem, M.; Herrmann, N.; Dinoff, A.; Mazereeuw, G.; Oh, P.I.; Goldstein, B.I.; Kiss, A.; Shammi, P.; Lanctot, K.L. Association between endothelial function and cognitive performance in patients with coronary artery disease during cardiac rehabilitation. Psychosom. Med. 2019, 81, 184–191. [Google Scholar] [CrossRef] [PubMed]
  95. Tarasova, I.V.; Trubnikova, O.A.; Barbarash, O.L. EEG and clinical factors associated with mild cognitive impairment in coronary artery disease patients. Dement. Geriatr. Cogn. Disord. 2018, 46, 275–284. [Google Scholar] [CrossRef] [PubMed]
Genes 13 01234 g001 550
Figure 1. The relationship between the telomere length of endotheliocytes and leukocytes.
Figure 1. The relationship between the telomere length of endotheliocytes and leukocytes.
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Genes 13 01234 g002 550
Figure 2. Flow chart diagram visualizing the database searches and the number of publications identified, screened, and the final full texts included in the present systematic review. Reason 1—there is no primary data on relative LTL in the article. Reason 2—the method of measuring relative LTL was carried out using an alternative method to the Ca. thon R. M. method. Reason 3—review and meta-analysis.
Figure 2. Flow chart diagram visualizing the database searches and the number of publications identified, screened, and the final full texts included in the present systematic review. Reason 1—there is no primary data on relative LTL in the article. Reason 2—the method of measuring relative LTL was carried out using an alternative method to the Ca. thon R. M. method. Reason 3—review and meta-analysis.
Genes 13 01234 g002
Genes 13 01234 g003 550
Figure 3. Median Relative Leukocyte Telomere Length in Patients with Coronary Heart Disease and Acute Myocardial Infarction Compared to Healthy Controls: AMI—acute myocardial infarction; CVDs—cardiovascular disease; CAD—coronary artery disease; LTL—leukocyte telomere length (CU—conventional units).
Figure 3. Median Relative Leukocyte Telomere Length in Patients with Coronary Heart Disease and Acute Myocardial Infarction Compared to Healthy Controls: AMI—acute myocardial infarction; CVDs—cardiovascular disease; CAD—coronary artery disease; LTL—leukocyte telomere length (CU—conventional units).
Genes 13 01234 g003
Table
Table 1. Mean Relative Telomere Length of Leukocytes in Adults without Cardiovascular Disease.
Table 1. Mean Relative Telomere Length of Leukocytes in Adults without Cardiovascular Disease.
Authors
[References]		Study
Characteristics		Group CharacteristicsParticipants
(n)		Age,
in Years
(M ± SE or
Me [P25; P75])		Sex
(Male/Female, %)		Method Telomere Length
Absolute,
bp		Relative (T/S Ratio), CU
Williet et al.,
2010 [55]		Prospective, population-based studyAustrians without CAD 71261.8 ± 10.847.6/52.4Real-
time quantitative PCR 		N/A1.52 ± 0.81
Dlouha et al.,
2016 [57]		Observational, cross-sectional case-control study Czechs without CAD64250 ± 2.70/100Real-time quantitative PCRN/A0.93 ± 0.38
Tian et al.,
2017 [58]		Observational, cross-sectional studyChinese without CAD 12848.5 ± 7.3357.8/42.2Real-
time quantitative PCR 		N/A 1.1 ± 0.57
Pejenaute et al.,
2020 [59]		Observational, cross-sectional studySpaniards without CAD 38954 ± 180/20Real-
time quantitative PCR 		8591 ± 84N/A
Gupta et al.,
2020 [60]		Observational, cross-sectional studyIndians without CVDs7734.38 ± 5.8675/25Real-
time quantitative PCR 		N/A 0.792
Starnino et al.,
2021 [61]		Observational, cross-sectional study Canadians without CVDs2555.68 ± 0.1956/44Real-
time quantitative PCR 		N/A 0.94 ± 0.15
Mazidi et al.,
2021 * [62]		Mendelian
randomized trial		British without CAD2022.3 ± 1.8100/0Real-time quantitative PCR12 420 ± 80N/A
Mazidi et al.,
2021 * [62]		Mendelian
randomized trial 		British without CAD2062.75 ± 2.1100/0Real-time quantitative PCR6 380 ± 60N/A
Hassler et al.,
2021 ** [56]		Observational, cross-sectional study Austrians without CVDs 9040.77 ± 11.62100/0Real-
time quantitative PCR		N/A0.7 ± 0.28
Hassler et al.,
2021 ** [56]		Observational, cross-sectional study Austrians without CVDs 9044.71 ± 10.960/100Real-
time quantitative PCR		N/A0.69 ± 0.31
Notes: bp—base pairs; CU—conventional units; N/A—no data; PCR—polymerase chain reaction. * There were two groups in the Mazidi study. One group of patients is young (mean age 22 years old), and the other group is elderly (mean age 62.75 years old). For each of the groups, this author calculated the relative LTL. ** There were two groups in the Hassler study: men and women without CVDs. Separately for each group, the author measured the relative LTL. Therefore, these results are listed in two rows of Table 1.
Table
Table 2. Mean Relative Telomere Length of Leukocytes in Adults with Stable Coronary Artery Disease.
Table 2. Mean Relative Telomere Length of Leukocytes in Adults with Stable Coronary Artery Disease.
Authors
[References]		Study
Characteristics 		Group CharacteristicsParticipants
(n)		Age,
in Years
(M ± SE or
Me
[P25; P75])		Sex
(Male/Female, %)		Method Telomere Length
Absolute,
bp		Relative (T/S Ratio), CU
Williet et al.,
2010 [55]		Prospective, population-based studyAustrians with a stable CAD 8870 ± 10.563.6/26.4Real-
time quantitative PCR 		N/A 1.13 ± 0.52
Yakhontov et al., 2017 * [64]Observational, cross-sectional study Russians with stable CAD
I-III FC		5952 [46.5; 55]100/0Real-
time quantitative PCR 		N/A 0.84
[0.2; 1.9]
Yakhontov et al., 2017 * [64]Observational, cross-sectional study Russians with stable CAD
I-III FC		4764
[62; 67]		100/0Real-
time quantitative PCR 		N/A 0.3
[0.09; 1.2]
Hammadah et al., 2017 [63]Observational, cross-sectional study Canadians with stable CAD56663 ± 9,063.6/26.4Real-
time quantitative PCR 		N/A 0.82 ± 0.14
Tian et al.,
2017 [58]		Observational, cross-sectional study Chinese with premature CAD12848.6 ± 7.2657.8/42.2Real-
time quantitative PCR 		N/A 0.88 ± 0.86
Yakhontov et al., 2018 [65]Observational, cross-sectional studyRussians with essential hypertension and stable CAD I-III FC4352
[46.5; 55.0] 		100/0Real-
time quantitative PCR 		N/A 0.7
[0.12; 0.92]
Pejenaute et al.,
2020 [59]		Observational, cross-sectional study Spaniards with coronary atherosclerosis11661 ± 188/12Real-
time quantitative PCR 		8315 ± 98N/A
Starnino et al.,
2021 [61]		Observational, cross-sectional study Canadians with stable CAD59866.13 ± 6.2580.6/19.4Real-
time quantitative PCR 		N/A 0.83 ± 0.18
Notes: bp—base pairs; CAD—coronary artery disease; CU—conventional units; N/A—no data; PCR—polymerase chain reaction; FC—functional class. * There were two groups in Yakhontov’s study: middle-aged patients with stable CAD (mean age—52 years) and elderly patients with stable CAD (mean age—64 years). LTL was determined for each group. Therefore, both groups studied by Yakhontov are included in Table 2.
Table
Table 3. Mean Relative Telomere Length of Leukocytes in Adults with Acute Myocardial Infarction.
Table 3. Mean Relative Telomere Length of Leukocytes in Adults with Acute Myocardial Infarction.
Authors
[References]		Study
Characteristics 		Group CharacteristicsParticipants
(n)		Age,
in Years
(M ± SE or
Me
[P25; P75])		Sex
(Male/Female, %)		Method Telomere Length
Absolute,
bp		Relative (T/S Ratio), CU
Russo A. et al.,
2012 [69]		Observational, open, cross-sectional, longitudinal study.Italians with AMI19940.1 ± 589.4/10.6Real-
time quantitative PCR 		N/A 0.77 ± 0.2
Dlouha, D. et al.,
2016 [57]		Observational, cross-sectional case-control studyCzechs with AMI50561 ± 9.70/100Real-
time quantitative PCR 		N/A 0.86 ± 0.32
Margaritis, M. et al.,
2017 [70]		Observational, open, cross-sectional, longitudinal studyBritish with AMI29063 ± 12.785.2/14.8Real-
time quantitative PCR 		N/A 1.08 [0.41—2.66] *
Gupta M.D. et al.,
2020 [60]		Observatio-nal, open, cross-sectional studyIndians with AMI7735.33 ± 6.2284.4/15.6Real-
time quantitative PCR 		N/A 0.115
Chan D. et al.,
2020 [71]		Prospective, observation, cohort,
longitudinal study.		British with AMI13581 ± 464/36Real-
time quantitative PCR 		N/A 0.47 ± 0.25
Notes: bp—base pairs; CU—conventional units; N/A—no data; PCR—polymerase chain reaction; *—median [P10—P90].
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Zimnitskaya, O.V.; Petrova, M.M.; Lareva, N.V.; Cherniaeva, M.S.; Al-Zamil, M.; Ivanova, A.E.; Shnayder, N.A. Leukocyte Telomere Length as a Molecular Biomarker of Coronary Heart Disease. Genes 2022, 13, 1234. https://doi.org/10.3390/genes13071234

AMA Style

Zimnitskaya OV, Petrova MM, Lareva NV, Cherniaeva MS, Al-Zamil M, Ivanova AE, Shnayder NA. Leukocyte Telomere Length as a Molecular Biomarker of Coronary Heart Disease. Genes. 2022; 13(7):1234. https://doi.org/10.3390/genes13071234

Chicago/Turabian Style

Zimnitskaya, Olga V., Marina M. Petrova, Natalia V. Lareva, Marina S. Cherniaeva, Mustafa Al-Zamil, Anastasia E. Ivanova, and Natalia A. Shnayder. 2022. "Leukocyte Telomere Length as a Molecular Biomarker of Coronary Heart Disease" Genes 13, no. 7: 1234. https://doi.org/10.3390/genes13071234

APA Style

Zimnitskaya, O. V., Petrova, M. M., Lareva, N. V., Cherniaeva, M. S., Al-Zamil, M., Ivanova, A. E., & Shnayder, N. A. (2022). Leukocyte Telomere Length as a Molecular Biomarker of Coronary Heart Disease. Genes, 13(7), 1234. https://doi.org/10.3390/genes13071234

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