Cardiometabolic profile and leukocyte telomere length in a black south african population

ABSTRACT Several studies have reported a possible association between leucocyte telomere length (LTL) and cardio-metabolic diseases (CMDs). However, studies investigating such association

are lacking in South Africa despite having a very high prevalence of CMDs. We investigated the association between LTL and CMD risk profile in a black South African population. This was a

cross-sectional study with participants > 21 years of age and residing in five townships in Cape Town. CMD markers were compared between men and women and across quartiles of LTL. Linear

and logistic regressions relate increasing quartile and Log10LTL with CMD risk profile, with appropriate adjustment. Among 676-participants, diabetes, obesity and hypertension prevalence

were 11.5%, 23.1% and 47.5%. Waist-circumference, hip-circumference and highly sensitive c-reactive protein values were significantly higher in women (all _p_ < 0.001), while HDL-C (_p_ =

 0.023), creatinine (_p_ = 0.005) and gamma glutamyl transferase (_p_ < 0.001) values were higher in men. In age, sex and BMI adjusted linear regression model, Log10 of LTL was associated

with low HDL-C (beta = 0.221; _p_ = 0.041) while logistic regression showed a significant association between Log10LTL and prevalent dyslipidaemia characterised by high LDL-C. In this

population, the relationship between LTL and CMD is weak given its association with only HDL-C and LDL-C. SIMILAR CONTENT BEING VIEWED BY OTHERS RELATIONSHIP BETWEEN AGING AND CONTROL OF

METABOLIC SYNDROME WITH TELOMERE SHORTENING: A CROSS-SECTIONAL STUDY Article Open access 19 October 2023 SARCOPENIC OBESITY IS ASSOCIATED WITH TELOMERE SHORTENING: FINDINGS FROM THE NHANES

1999–2002 Article Open access 04 November 2021 COMPARISON OF TRIGLYCERIDE-GLUCOSE RELATED INDICES IN PREDICTION OF CARDIOMETABOLIC DISEASE INCIDENCE AMONG US MIDLIFE WOMEN Article Open

access 03 June 2025 INTRODUCTION Telomeres are specialized chromosomal DNA–protein structures that make up the terminal regions of chromosomes and are formed of a highly conserved hexameric

(TTAGGG) tandem repeat DNA sequence. Their primary function is to protect and stabilize the genetic material carried by chromosomes in several ways. They shield the chromosomal termini from

recognition by the DNA damage response system of the cell, cap chromosome ends thereby preventing them from being degraded or fused together. The length of the telomere is longest at birth

and begins to decline within the first 6 weeks of life. In addition to chronological age, there is a wide range of genetic and environmental factors modulating telomere length (TL). Gender1,

ethnicity2 and level of physical activity3 have been shown to modulate TL. Moreover, short TL has been shown to be associated with type 2 diabetes in Caucasian, South Asian and

Afro-Caribbean4, Insulin Dependent Diabetes Mellitus (IDDM) in white American men5, gestational diabetes mellitus in Chinese population6, coronary artery disease in Chinese men7, vascular

dementia in German population8, cardiovascular disease9,10 and hypertension11 in the Adult United State population. This large body of evidence therefore suggests that there is a possible

relationship between TL and cardiometabolic diseases (CMDs). South Africa is facing a quadruple burden of diseases including infectious diseases such as HIV and tuberculosis; maternal and

child conditions; non-communicable diseases (NCDs); and violence, injuries and trauma12. CMDs, the leading NCDs, are among the top ten causes of death in South Africa12. Accordingly,

identification of biomarkers of CMDs is essential for early diagnosis and appropriate management of these conditions especially in black South Africans marked by higher prevalence of CMDs.

Given that CMDs have been shown to be associated with leucocyte telomere length (LTL) in European, American and Asian populations, we therefore undertook this study to investigate the

association between LTL and cardio-metabolic profile in a black South African population. RESULTS Out of the 1116 participants examined in this study, DNA extracted from stored samples for

analysis were available for 676 participants. This number resulted from samples with LTL values which could only be quantified on good quality DNA sample (absorbance 260 nm/280 nm ratio

between 1.7 and 2.0). The prevalence of the cardiometabolic disorders was 47.5% for obesity, 23.1% for hypertension and 11.5% for type 2 diabetes (Table 1). Weight, BMI, heart rate, WC, HC

and hs-CRP (all _p_ < 0.001) median values were higher in women than men while height (_p_ < 0.001), HDL-C (_p_ = 0.023), creatinine (_p_ = 0.005) and GGT (_p_ < 0.001) values were

significantly higher in men than women (Table 1). Moreover, more women than men were obese by all parameters measured [BMI (_p_ < 0.001), WC (_p_ < 0.001), WHR (_p_ = 0.012) and WHtR

(_p_ < 0.001)] and had dyslipidaemia [high triglycerides (_p_ = 0.003), high LDL-C values (_p_ = 0.009) and high non-HDL-C values (_p_ = 0.03)]. The distribution of TL was skewed to the

right (skewness = 3.45), indicating that TL values were not normally distributed (Fig. 1A). In order to have a normal distribution of TL, it was Log10 transformed (Fig. 1B). Correlation

analysis showed a significant positive association between LTL and HDL-C (r = 0.082, _p_ = 0.034) (Fig. 2A). In women, LTL was negatively correlated with LDL-C (r =  − 0.1, _p_ = 0.037)

(Fig. 2B) and non-HDL-C (r =  − 0.101, _p_ = 0.034) (Fig. 2C). In men, there was a significant positive correlation between LTL and Urea (r = 0.179, _p_ = 0.007) (Fig. 2D). The association

between LTL and cardiometabolic profile was investigated by categorizing the LTL values into quartiles with the first being the lowest and the fourth being the highest (Table 2). Amongst the

different cardio-metabolic parameters investigated, quartiles of LTL were shown to be positively and significantly associated with HDL-C (Table 3). Linear regression carried out in age and

sex adjusted model showed a significant association between Log10 LTL and HDL-C (beta = 0.028; _p_ = 0.041) (Table 4) while increasing quartiles of LTL was not associated with HDL-C in

linear regression models with similar levels of adjustment. Neither increasing quartiles of LTL nor Log10 LTL was associated with other cardio-metabolic parameters in age and sex adjusted

linear regression models. In logistic regressions, there were no associations between quartiles of LTL and diabetes, hypertension, any dyslipidaemia and obesity variables. However, when LTL

was Log transformed, there was a significant association between Log10 LTL and prevalent dyslipidaemia with High LDL-C > 3.0 mmol/L (OR = 0.41, _p_ = 0.045) (Table 5). DISCUSSION This

study examined the associations of LTL with cardiometabolic variables of adiposity, hypertension, type 2 diabetes and dyslipidaemia in a black urban South African population. Linear

regression carried out in age and sex adjusted model showed a significant association between Log10LTL and HDL-C as continuous variable. In logistic regression model, Log10LTL was associated

with prevalent dyslipidaemia characterized by high LDL-C. Correlation analysis showed that LTL was associated with Total Cholesterol and non-HDL-C in women and urea in men. However, neither

quartiles of LTL nor Log transformed values were associated with hypertension, obesity and type 2 diabetes, which was surprising and warrants further exploration in this population. The

association between LTL and some lipid parameters in the study suggests a possible but weak relationship between shortened TL and dyslipidaemia. Similar results were obtained in the United

States13 and in Iran14. Dyslipidaemia, characterised by altered serum lipid levels is associated with several disease conditions including coronary heart disease, hypertension, diabetes,

obesity and oxidative stress which is related with LTL shortening. Although most published literature reported a positive association between short telomere length and a high prevalence of

diabetes, obesity, hypertension and other cardiovascular diseases, in this study there were no associations between LTL with diabetes, hypertension or obesity. A meta-analysis of multiple

studies found a significant negative association between LTL and diabetes15 while a systematic review reported a weak to moderate association between obesity and telomere length16. Short TL

was also positively correlated with high SBP and DBP11, high fasting glycaemia17, altered lipid profile markers6 and cardiovascular diseases10,18,19,20. The proposed pathway of the

association between shortened TL and CMDs reported is bi-directional with cardio-metabolic diseases causing shortening of telomere length and short telomere length increasing the risk of

cardio-metabolic diseases. However, these studies have all been carried out in European, Asian and American population, with no studies from Africa, suggesting that the lack of association

in our study could be as a result of population differences. Moreover, the sample size of these cross-sectional studies and systematic reviews/meta-analysis was large enough (minimum > 

5000) compared to 676 in our study. Therefore, their studies had more power to detect differences compared to our study. It is possible that LTL could also be determined by the origin and

evolution of individuals. Hansen reported shorter TL in Europeans and African Americans originating from Western Africa compared to those living in Africa originating from Tanzania (Eastern

Africa)21. These results are consistent with other studies reporting longer telomere length in Black Africans compared to white Europeans and Americans in both children and

adult22,23,24,25,26,27. However, TL was observed to be longer in white compared to black teachers in South Africa28. In this South African population, the risk of cardiovascular disease was

higher in black teachers that white teachers28. These results shows that genetic differences between ethnic groups and environmental factors ‘contribute’ to overall telomere length. Unlike

this study findings showing no association between TL and age, several studies have reported a significant negative correlation between TL and chronological age. TL shortens with age and age

associated disorders. A systematic review showed an average decrease of 21.91 base pair TL/year across cross-sectional studies and 32.2–45.5 base pair TL/year in 5 longitudinal studies29.

Another important factor that affects TL is sex with several studies showing TL to be longer in women than men9,30,31,32,33. However, in the present study there was no association between

LTL and gender. Even though the present study was carried out in an African population which is different from studies reporting an association between TL and age/gender (Asia, Europe and

USA) and could probably explain the difference in the results, further research is needed to explore these associations in Africans. Moreover, the black South African population in which the

study was carried out is genetically diverse with some having gene flow from Europe, East Africa and South Asia34. This genetic diversity in the study population could be responsible for

the difference in the results obtained. The cross-sectional design of the study prevents conclusions on a causal relationship between LTL and the CMD risk factors investigated. The small

sample size of the study and the low sample realisation in men (34%) characteristic of epidemiological studies in this country and probably due to their reluctance to participate,

particularly for the drawing of blood samples is another limitation. In this study, multiple hypothesis testing (MHT) was not performed. As such, the results would not withstand a stringent

MHT based correction which constitute a possible limitation. In a black urban South African population, LTL was weakly associated with HDL-C and LDL-C, but not with diabetes, hypertension or

obesity. Although the association of LTL with cardiometabolic risk factors have been reported in many populations, there is a paucity of data in African populations. Further research,

particularly in longitudinal studies, is required to clearly elucidate the relationship between LTL and CMDs in Africans. MATERIALS AND METHODS STUDY SITE AND POPULATION Participants

consisted of > 21 years old black men and women residing in Cape Town. This cross-sectional study titled Cardiovascular Risk in Black South Africans (CRIBSA) was conducted in 2008–2009

with data collected by a 3-stage cluster sampling as previously described35. This sampling technique was used with quotas, which were pre-specified by age and sex categories to ensure a

representative sample, Recruitment took place during office hours and those excluded were the following: pregnant and lactating women, individuals who were bedridden, unable to give consent,

on tuberculosis treatment, on antiretroviral therapy, cancer patients having received treatment within the last year and individuals residing in Cape Town for less than three months. Ethics

approval was obtained from the South African Medical Research Council’s Human Research Ethics Committee (EC026-9/2016) and the University of Cape Town’s Research and Ethics Committee

(224/2006), and informed consent was obtained from all participants. The research was performed in accordance with the declaration of Helsinki and all methods carried out with relevant

guidelines and regulations. DATA COLLECTION Data, which were collected by trained fieldworkers, included administered questionnaires, clinical examinations and biochemical analyses. Clinical

examinations comprised anthropometry (height, weight, and waist and hip circumferences) and blood pressure (BP) measured using standard techniques36. A calibrated scale was used to measure

weight to the nearest 0.5 kg with each participant barefoot and in light clothing. A stadiometer was used to measure height to the nearest 0.1 cm. A flexible tape measured waist and hip

circumferences to the nearest 0.1 cm. For waist circumference (WC), the tape was placed approximately 2 cm above the umbilicus while hip circumference (HC) was measured at the maximum

posterior protuberance of the buttocks with the participant standing upright with feet together. Three BP measurements were taken at intervals of 2 min, using an Omron BP monitor after the

participant had been rested for at-least 5 min. The average of the second and third BP measurements was used for analysis. After an overnight fast of approximately 10 h, blood samples were

collected by venepuncture into EDTA and dry tubes and a portion processed for biochemical analysis. Plasma glucose (hexokinase) was measured using a colorimetric method according to the

manufacturer’s protocol. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and triglycerides were measured in serum using standard enzymatic techniques37,38,39.

Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald formula40, while non-HDL-C was calculated using the formula: TC–HDL-C. An oral glucose tolerance test (OGTT)

was administered with blood samples collected 2 h after a glucose load41. All colorimetric measurements were conducted using a Beckman Coulter AU 500 spectrophotometer. Serum creatinine

(CAYMAN CHEMICAL), gamma glutamyl transferase (Abcam) and highly sensitive c-reactive protein (hs-CRP) (BIOMATIK ELISA) measurements were conducted on stored serum samples according to the

manufacturer’s protocol. TL assay was conducted from DNA samples extracted from whole blood stored at −80 °C in EDTA tubes using the salt extraction technique. Briefly, 5 mL blood samples in

EDTA tubes were defrosted to room temperature and poured into a 50 mL centrifuge tube. Thirty mL lysis buffer (see supplementary material) was added, and red blood cells were lysed by

incubation on ice and vortexing. After lysis of red blood cells, the pellets were washed thrice with phosphate buffered saline (see supplementary material) which was later discarded. The

pellets were then incubated with nuclear lysis buffer (see supplementary material) overnight at 60 °C. The next day, the supernatant was collected, and the proteins precipitated using 1 mL

saturated sodium chloride (6 M) solution. The supernatant containing the DNA was collected into new 15 mL centrifuge tubes and absolute ethanol added to precipitate the DNA by inversion.

Precipitated DNA was removed and washed with 70% ethanol. After washing, the precipitate was dissolved in Tris Ethylene Diamine Tetra-Acetate buffer (see supplementary material) and the

concentration and quality of the DNA measured using a Nano drop. All samples with absorbance 260 nm/280 nm ratio from 1.7 to 2 were diluted to 5 mg/mL using polymerase chain reaction (PCR)

grade water and TL measured by quantitative real time PCR using the method described by O’Callaghan and Fenech42. Serial dilutions of the telomere standard and the single copy gene (36B4)

standard were made as described by O’Callaghan and Fenech42. A master mix solution containing Power SYBR I (AmpliTaq Gold DNA polymerase, dNTPs, SYBR I Green Dye, optimised buffers and

passive reference dye (ROX) (10μL, 1×)), forward primer (1μL, 0.1 μM), reverse primer (1μL, 0.1 μM) and ddH2O (4uL) was prepared, mixed well and briefly centrifuged. Using a multichannel

pipetted, 16 μL master mix solution were pipetted into each well of a 96 well plate. Into the corresponding wells were added 4 μL each of DNA sample, standards, positive and non-template

control (distilled water) in duplicates. The plate was sealed with an optical clear film, centrifuged briefly and run in a QuantStudio 7 Flex Real Time PCR Thermocycler using the following

PCR conditions; 10 min at 95 °C, followed by 40 cycles of 95 °C for 15 s 60 °C for 1 min, followed by a dissociation (or melt) curve. At the end of the run, the plate was removed and

discarded. Each sample was amplified twice, using telomere forward and reverse primers and the single copy gene forward and reverse primers. After amplification was completed the AB software

produced a value for each reaction that is equivalent to kb/reaction based on the telomere standard curve values. The kb/reaction for telomere and genome copies/reaction for diploid genome

copy values were exported and used to calculate the LTL in kilobase (kb) as follows; LTL = 

\(\frac{{{\text{telomere}}\;{\text{kilobase}}\;{\text{per}}\;{\text{reaction}}\;{\text{value}}}}{{{\text{diploid}}\;{\text{genome}}\;{\text{copy}}\;{\text{number}}}}\). DEFINITIONS Body mass

index (BMI), calculated as weight (kg)/height (m) squared, classified participants into three categories of generalised adiposity: normal weight (18 ≤ BMI < 25 kg/m2), overweight (25 ≤ 

BMI < 30 kg/m2) and obese (BMI ≥ 30 kg/m2)43. Central obesity was determined using the following criteria: WC > 94 cm in men and > 80 cm in women, waist-to-hip ratio (WHR) ≥ 0.9 in

men and ≥ 0.85 in women44 or waist-to-height ratio (WHtR) > 0.545. Hypertension was defined as systolic BP (SBP) ≥ 140 mmHg or diastolic BP (DBP) ≥ 90 mmHg or known hypertension on

treatment46. Dyslipidaemia was defined as TC > 5 mmol/l, triglycerides > 1.5 mmol/L, HDL-C < 1.2 mmol/L, LDL-C > 3.0 mmol/L and non-HDL-C > 3.37 mmol/L or taking anti-lipid

agents47. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/L and/ or 2-h post glucose load ≥ 11.1 mmol/L, previously diagnosed or taking antidiabetic medications41. STATISTICAL

ANALYSIS Data analysis was carried out using SPSS Version 21 software. Continuous variables are presented as medians (25th to 75th percentiles) and categorical variables as counts

(percentages). Mann Whitney U test was used to compare baseline characteristics by sex. TL was categorised into quartiles and the linear trend in CMD profile (continuous variables) across

the different quartiles of TL was computed using the median test. Similarly, chi square test was computed and the linear-by-linear association used to compare the trend in proportions of

disease conditions (categorical variable) across the quartiles of TL. Spearman correlation was used to assess the association between quartile of TL and cardio-metabolic parameters. The

interactions between TL categories and cardio-metabolic risk profile were tested using linear and logistic regressions, by incorporating in the same model the main effects of the variables

of interest as well as their interaction term with TL. In linear and logistic regression analyses, TL was log transformed. A _p_ value < 0.05 was considered statistically significant.

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participants, fieldworkers, SAMRC research nurse fieldworkers Debbie Jonathan and Theresa Gogela, fieldwork coordinator Erica April, study manager Serena van Haght, and statisticians Nomonde

Gwebushe, Rebecca Shanmugam and Ria Laubscher. FUNDING This work was supported by the South African Medical Research Council (SAMRC): SAMRC-RFA-IRF-02-2016; an unrestricted grant from

Servier Laboratories (South Africa); the Initiative for Cardiovascular Health Research in Developing Countries (IC Health) Foundation Council; and Brigham and Women’s Hospital, Harvard

University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS *

Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé 1, Yaoundé, Cameroon Ndonwi Elvis Ngwa & Eugene Sobngwi * South African Medical Research

Council/Cape Peninsula University of Technology Cardio-Metabolic Health Research Unit, Department of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University

of Technology, Cape Town, South Africa Ndonwi Elvis Ngwa & Tandi E. Matsha * Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa Carl Lombard * Chronic

Disease Initiative for Africa, Department of Medicine, UCT, Cape Town, South Africa Naomi Levitt * Non-Communicable Diseases Research Unit, South African Medical Research Council, Durban,

Cape Town, South Africa Andre-Pascal Kengne & Nasheeta Peer * Department of Medicine, University of Cape Town, Cape Town, South Africa Andre-Pascal Kengne & Nasheeta Peer * Division

of Epidemiology and Biostatistics, Department of Global Health, University of Stellenbosch, Cape Town, South Africa Carl Lombard Authors * Ndonwi Elvis Ngwa View author publications You can

also search for this author inPubMed Google Scholar * Tandi E. Matsha View author publications You can also search for this author inPubMed Google Scholar * Carl Lombard View author

publications You can also search for this author inPubMed Google Scholar * Naomi Levitt View author publications You can also search for this author inPubMed Google Scholar * Eugene Sobngwi

View author publications You can also search for this author inPubMed Google Scholar * Andre-Pascal Kengne View author publications You can also search for this author inPubMed Google

Scholar * Nasheeta Peer View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS The authors confirm contribution to the paper as follows:

conception and design; N.P. and A.P.K. conceived and designed the study, E.N.N. carried out the research work, prepared the draft manuscript, analysis and interpretation of results, T.M. and

A.P.K. supervised the research work, T.M., C.L., N.L. reviewed the results and all authors approved the final version of the manuscript. CORRESPONDING AUTHOR Correspondence to Ndonwi Elvis

Ngwa. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER'S NOTE Springer Nature remains neutral with regard to

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this licence, visit http://creativecommons.org/licenses/by/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Ngwa, N.E., Matsha, T.E., Lombard, C. _et al._ Cardiometabolic

profile and leukocyte telomere length in a Black South African population. _Sci Rep_ 12, 3323 (2022). https://doi.org/10.1038/s41598-022-07328-8 Download citation * Received: 15 July 2021 *

Accepted: 31 January 2022 * Published: 28 February 2022 * DOI: https://doi.org/10.1038/s41598-022-07328-8 SHARE THIS ARTICLE Anyone you share the following link with will be able to read

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