INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)

ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025

Comparative Study of Myocardial BiomarkersAmong Womenwith and

Without Polycystic Ovarian Syndrome (Pcos) in Nigeria

*¹Ohikere, O. P., ²Mokwenye, N. V., ³Emokpae A. M., ⁴Ige, I. P., (ORCID) ⁵Adewole, A. A. (ORCID)

^1,2,Department of Medical Laboratory Science, Igbinedion University, Okada, Edo State, Nigeria.

³Department of Medical Laboratory Science, University of Benin, Benin City, Edo State, Nigeria.

⁴Department of Medical Laboratory Science, School of Basic Medical Sciences, Federal University of

Technology, Akure, Ondo State, Nigeria.

⁵Obstretics and Gynaecology department, Federal Teaching Hospital, Lokoja, Kogi State, Nigeria.

*Corresponding Author:

DOI: https://dx.doi.org/10.51244/IJRSI.2025.12110097

Received: 25 November 2025; Accepted: 01 December 2025; Published: 10 December 2025

ABSTRACT

Polycystic Ovarian Syndrome (PCOS) is a common endocrinopathy associated with chronic low-grade

inflammation, insulin resistance, and dyslipidemia, all of which elevate the long-term risk of cardiovascular

disease (CVD). While subclinical myocardial injury is recognized in Western populations with PCOS, data from

Nigerian women, who may face distinct genetic and environmental risk factor profiles, remain scarce. This study

aims to compare the circulating levels of specific myocardial injury biomarkers between Nigerian women with

and without PCOS. This was a case-control study conducted at selected healthcare centers and fertility clinics in

Lokoja, Okene, and Anyigba, Kogi State, Nigeria, where PCOS cases are commonly reported. This study

comprises of 150 samples, with 110 women diagnosed with PCOS based on the Rotterdam criteria (PCOS

Group) were recruited and compared to 40 age- and BMI-matched healthy women (Control Group). Fasting

blood samples were analyzed for quantitative measurement of three cardiac biomarkers: Myoglobin (MYO),

Cardiac Troponin I (cTnI), and Creatine Kinase-MB (CK-MB). Anthropometric data and standard lipid

profiles were also collected. Data were analyzed using independent samples t-tests and multivariate analysis of

variance (MANOVA), with significance set at p < 0.05. The multivariate test using Pillai’s Trace indicated a

significant overall group effect, V = 0.202, F(3, 146) = 12.32, p < 0.001, partial η² = 0.202, suggesting that the

combined biomarker profile differed between groups. Follow-up univariate ANOVAs revealed that women

with PCOS had significantly higher mean serum levels of cTnI (F(1,148) = 5.91, p = .016, partial η² = 0.038),

CK-MB (F(1,148) = 20.43, p < 0.001, partial η² = .121), and MYO (F(1,148) = 21.65, p < .001, partial η² =

0.128) compared to controls. The estimated marginal means confirmed consistently elevated concentrations of

all three biomarkers in the PCOS group (MYO: 57.88 ± 3.51 ng/ml; CK-MB: 1.87 ± 0.08 ng/ml; cTnI: 0.074 ±

0.005 ng/ml) relative to the control group (MYO: 26.28 ± 5.82 ng/ml; CK-MB: 1.21 ± 0.13 ng/ml; cTnI: 0.053

± 0.008 ng/ml). Collectively, these findings indicate that PCOS is associated with significantly elevated serum

concentrations of myocardial biomarkers, suggesting the presence of early or subclinical myocardial stress in

affected women, independent of age matching. Furthermore, regression analysis suggested that significant

factor, like MYO was an independent predictor of the outcome variable. Nigerian women with PCOS exhibit

significantly elevated circulating levels of myocardial biomarkers (MYO, cTnI, and CK-MB), suggesting the

presence of chronic, subclinical myocardial injury in this population. These findings underscore the need for

early and aggressive cardiovascular risk assessment and management strategies for women with PCOS in the

Nigerian clinical setting.

Keywords: Myocardial, PCOS, Hyperinsulinemia, Endocrine, Metabolic, BMI

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INTRODUCTION

Background of the Study

Polycystic ovary syndrome (PCOS) is a common endocrine–metabolic disorder of reproductive-age women

characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Beyond

reproductive consequences, PCOS is associated with adverse cardiometabolic features like insulin resistance,

dyslipidaemia, obesity and hypertension which increase long-term cardiovascular disease (CVD) risk. Recent

reviews and research studies have therefore indicated that PCOS as a “risk-enhancing” condition for future

cardiovascular events (1). PCOS is a heterogeneous endocrine disorder of reproductive-age women diagnosed

using accepted criteria like Rotterdam criteria: presence of two of three: oligo/anovulation, clinical/biochemical

hyperandrogenism, polycystic ovarian morphology after exclusion of secondary causes (1).

Myocardial biomarkers for example high-sensitivity cardiac troponins (cTnI), creatine kinase-MB (CK-MB),

myoglobin (MYO) and natriuretic peptides are widely used to detect myocardial injury and to stratify

cardiovascular risk in clinical practice. Sex differences in baseline cardiac troponin concentrations and the

prognostic value of low-level troponin in women have been described, to assess the need for sex-specific

consideration when interpreting biomarker data. In parallel, biomarker panels and proteomic approaches have

been used recently to identify cardiovascular-risk proteins that may be dysregulated in PCOS and could provide

early signals of cardiac risk before overt disease develops (2). Myocardial biomarkers are blood analytes used

to detect myocardial injury or strain. In this study the term refers primarily to high-sensitivity cardiac troponin

(hs-cTnI or hs-cTnT), creatine kinase-MB (CK-MB) isoenzyme, andmyoglobin (MYO). These markers differ

in kinetics and specificity: troponins are most specific for cardiomyocyte injury, CK-MB rises in acute myocyte

necrosis but is less specific, and natriuretic peptides reflect myocardial wall stress (3).

Insulin resistance (HOMA-IR) is a homeostatic Model Assessment of Insulin Resistance, calculated from fasting

glucose and insulin, used here as a continuous variable to quantify insulin resistance. Elevated HOMA-IR is

common in PCOS and is a mediator of cardiometabolic risk (4). Cardiometabolic risk factors are traditional risk

variables for CVD including obesity (BMI and waist circumference), dyslipidaemia (elevated LDL-C,

triglycerides; low HDL-C), hypertension, impaired fasting glucose, and insulin resistance.

The international and regional evidence linking PCOS to elevated cardiometabolic risk and to disorder in

cardiovascular biomarkers, but there is a scarcity of direct comparisons of myocardial biomarker levels in

Nigerian women with and without PCOS. This study will measure and compare established myocardial

biomarkers in these groups, examine their associations with metabolic risk factors, and thereby provide

population-specific data to inform screening and preventive care (4).

Although metabolic and anthropometric determinants of CVD risk in PCOS have been studied in many

populations, data from sub-Saharan Africa, and Nigeria in particular remain relatively limited. A small but

growing number of Nigerian studies report elevated cardiometabolic risk among women with PCOS, suggesting

that PCOS may independently increase cardiovascular risk in this setting. However, few published investigations

have directly compared myocardial biomarker concentrations between Nigerian women with and without PCOS,

or examined how these biomarkers relate to metabolic variables such as BMI, insulin resistance, lipids in that

population. This gap is important because population-specific baseline biomarker distributions and risk profiles

influence the interpretation and clinical utility of myocardial biomarkers (5).

Taken together, the literature motivates a focused comparative study of myocardial biomarkers among Nigerian

women with and without PCOS to (1) determine whether subclinical myocardial injury or higher biomarker

concentrations are present in PCOS, (2) explore relationships between biomarkers and cardiometabolic risk

factors in this population, and (3) provide locally relevant data that could inform screening and preventive

strategies. The present study is therefore placeed to address these gaps by measuring established cardiac

biomarkers: high-sensitivity cardiac troponin, CK-MB, and myoglobin and associating them to clinical and

laboratory measures of cardiometabolic risk.

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The aim and objectives of this studyare to evaluates serum levels of myoglobin, CK-MB, and cTnI in Nigerian

women with Polycystic Ovarian Syndrome (PCOS) versus age-matched controls to assess cardiovascular risk.

It also investigates correlations between these biomarkers and cardiometabolic indices, insulin resistance, and

anthropometric parameters. Furthermore, the research analyzes the combined expression of these markers to

detect subclinical myocardial stress. Ultimately, the study aims to establish the clinical value of these biomarkers

as early predictors of cardiovascular disease risk within the Nigerian PCOS population. The objectives of this

study are to: compare concentrations of myocardial biomarkers (high-sensitivity cardiac troponin, CK-MB, and

myoglobin (MYO) between reproductive-age Nigerian women diagnosed with PCOS and age-matched women

without PCOS; assess the association between myocardial biomarker levels and cardiometabolic risk factors

(BMI, waist circumference, fasting glucose/insulin, HOMA-IR, lipid profile, and blood pressure) within the

PCOS group and within controls; determine whether PCOS status predicts elevated myocardial biomarkers after

adjustment for conventional cardiometabolic risk factors; and to estimate the prevalence of clinically meaningful

elevations in myocardial biomarkers among women with PCOS in the study sample.

This study is so important since PCOS is associated with excess cardiometabolic risk factors that predispose to

ischemic heart disease and heart failure later in life. Early identification of subclinical myocardial injury or

biomarker changes could permit targeted risk-reduction in a high-risk group (1). Most biomarker research in

PCOS has been performed in high-income countries; Nigeria and other sub-Saharan African populations are

under-represented despite potentially different obesity patterns, genetic backgrounds, and access to care that can

modify risk and biomarker distributions. Locally generated data are therefore essential for guideline-relevant

interpretation (5). If PCOS is associated with higher myocardial biomarkers independent of traditional risk

factors, this would strengthen recommendations for routine cardiometabolic screening in Nigerian women with

PCOS and could inform public-health strategies. Biomarker findings may also prompt longitudinal follow-up

studies to clarify prognostic implications (6).

Some questions to be addressed in this research work include: do Nigerian women with PCOS have higher

concentrations of high-sensitivity cardiac troponin, CK-MB, or myoglobin (MYO) compared with age-matched

women without PCOS? What are the relationships between myocardial biomarker levels and cardiometabolic

risk factors (BMI, waist circumference, insulin resistance, lipids, blood pressure) in women with PCOS and in

controls? Does PCOS status independently predict elevated myocardial biomarker concentrations after

controlling for conventional risk factors?

LITERATURE REVIEW

Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy affecting women of reproductive

age globally, characterized by hyperandrogenism, menstrual dysfunction, and polycystic ovarian morphology

(7). Importantly, PCOS is essentially connected to a high prevalence of Insulin Resistance (IR), a condition

where cells do not respond effectively to insulin, leading to compensatory hyperinsulinemia (8). PCOS is the

most widespread endocrine metabolic disorder affecting 5-10% of women of reproductive age worldwide. (9).

PCOS is related to complication existing across lifespan starting from reproductive and dermatological concerns

to metabolic and psychological complication such as diabetes, metabolic syndrome, cardiovascular disorder etc,

(10). PCOS can lead to cardiometabolic risk, meaning that women with PCOS frequently have insulin resistance,

dyslipidemia, and hypertension; classical risk factors for atherosclerotic cardiovascular disease (ASCVD).

Several systematic reviews and cohort studies have reported higher prevalence of cardiometabolic risk markers

and some evidence for elevated cerebrovascular/cardiac event risk, though the magnitude and independence of

risk vary across studies and phenotypes. (11)

Recent population work in Nigeria estimates that PCOS affects roughly 8–9% of reproductive-aged women,

although prevalence depends on diagnostic criteria and sampling frame, and underdiagnosis remains a persistent

problem (12). Women with PCOS show a higher prevalence of established cardiovascular risk factors like insulin

resistance, central obesity, dyslipidaemia, hypertension, and chronic low-grade inflammation which together

accelerate atherosclerotic processes and increase lifetime CVD risk (13; 14).

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Pathophysiology

Polycystic ovary syndrome (PCOS) is multifactorial with interacting endocrine, metabolic, genetic, and

environmental contributors such as Hyperandrogenism (ovarian and/or adrenal), Insulin resistance and

compensatory hyperinsulinemia which is dependent on body mass index (BMI), Ovarian dysfunction, Chronic

low-grade inflammation and oxidative stress, Genetic and developmental components, and Adiposity and ectopic

fat. Specifically, PCOS emerges from a confluence of hyperandrogenism, intrinsic or acquired insulin resistance,

ovarian dysfunction, and environmental modifiers, creating variable clinical phenotypes (15; 16).

Epidemiology

Prevalence estimates vary by population and diagnostic criteria but generally range from about 6% to 20% of

women of reproductive age depending on the criteria used and population studied. PCOS often first becomes

apparent in adolescence and is a major cause of anovulatory infertility worldwide (16). Polycystic ovary

syndrome (PCOS) is the most common endocrine disorder among women and so peculiar between the ages of

18 and 44 (17). According to the World Health Organization (WHO), PCOS affects over 6 to 13% of

reproductive-aged women (18). Polycystic ovary syndrome (PCOS) is a common condition affecting

approximately 8% of women. Once someone is infertile due to lack of ovulation, PCOS is the most common

cause and could be a pointer to patients' diagnosis. The 2022 approximations of prevalence of PCOS vary which

could arises in between 5% and 18% of women (19).

The occurrence of PCOS depends on the choice of diagnostic criteria. Using the Rotterdam criteria, around 10–

13% of women have PCOS (17). Based on the NIH standards, by using the Androgen Excess Society criteria,

the global frequency was 5.5%, growing to approximately 7.1%. Irrespective of the criteria, the prevalence of

PCOS is increasing, likely due to an aging population, more awareness, and increasing obesity rates (20).

Incidence appears impartially even among people with different ethnicities, but is conceivably higher in people

from South East Asia and the Eastern Mediterranean (17). PCOS may express differently however. For instance,

in African and Hispanic American people with PCOS, there is more insulin resistance compared to other ethnic

groups (21). The same is true for South Asian people with PCOS, who also have more metabolic symptoms and

higher BMIs. East Asian women typically have less hirsutism and lower BMI compared to other groups (19).

Ultrasonographic findings of polycystic ovaries are found in 8–25% of women who are not affected by the

syndrome. 14% women on oral contraceptives are found to have polycystic ovaries. Ovarian cysts are also a

common side effect of levonorgestrel-releasing intrauterine devices (IUDs).

Hormonal And Metabolic Dysregulation of PCOS

PCOS marker include hormonal imbalance, particularly hyperandrogenism, resulting from disruption of the

hypothalamic–pituitary–ovarian (HPO) axis. Increased GnRH pulse frequency elevates luteinizing hormone (LH)

while follicle-stimulating hormone (FSH) remains normal or slightly reduced. Excess LH stimulation of ovarian

theca cells leads to elevated androgen production (22). This hyperandrogenic environment impairs follicular

development, leading to polycystic ovarian morphology (PCOM), anovulation, and menstrual irregularities. In

addition, granulosa cells from these follicles produce elevated AMH, which further inhibits aromatase activity,

reducing estrogen production and perpetuating follicular arrest (23; 24). Metabolic dysfunction is another central

component. Insulin resistanceexisting in both lean and obese phenotypesdrives compensatory hyperinsulinemia.

Elevated insulin suppresses hepatic SHBG production, thereby increasing bioavailable androgens. Chronic low-

grade inflammation further exacerbates insulin resistance, forming a vicious cycle between reproductive and

metabolic disturbances (25; 26).

Polycystic Ovarian Syndrome (PCOS) and Myocardial Biomarkers

Clinical significance of the presence of elevated myocardial biomarkers in PCOS women provides an essential

instrument for early risk classification. These markers serve as measurable evidence that the metabolic and

hormonal dysfunction of PCOS is translating into direct, measurable cardiac consequences, necessitating

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aggressive management of IR, weight, and dyslipidemia to mitigate long-term CVD risk (7). The relationship

between PCOS and myocardial biomarkers centers on the heightened metabolic and inflammatory stress induced

by the syndrome, leading to subclinical myocardial injury detectable by these markers. PCOS is recognized not

just as a reproductive disorder, but as a major cardiovascular risk factor (7).

The Pathophysiological Linkage

The chronic state associated with PCOS drives the release of cardiac biomarkers through several mechanisms,

which has demonstrated a significant correlations with several published studies. This include:

Insulin Resistance (IR) and Inflammation: PCOS is strongly associated with IR and chronic low-grade

inflammation. Adipose tissue, particularly visceral fat, releases pro-inflammatory cytokines like interleukine 6

(IL-6), and tissue necrosis factor (TNF) that cause systemic endothelial dysfunction and directly damage the

myocardium (7).

Oxidative Stress: Increased oxidative stress, stemming from dysregulated metabolism, contributes to cellular

damage in the heart muscle (27).

Myocardial Stress: The hypertension and dyslipidemia often accompanying PCOS increase the mechanical and

hemodynamic load on the heart, leading to myocardial stress and potential hypertrophy (28).

These chronic stresses, even in the absence of acute coronary events, result in the measurable leakage of specific

cardiac proteins into the circulation.

Cardiac Troponin I and T (cTnI and cTnT):

Cardiac Troponin I and T (cTnI and cTnT) are the most specific markers of myocardial necrosis (29). In women

with PCOS, even high-sensitivity, chronically elevated levels of these troponins have been observed compared

to healthy controls (27). This chronic low-level elevation is considered a powerful indicator of subclinical

myocardial injury and stress, independently predicting future adverse cardiac events like heart failure and

myocardial infarction, even in asymptomatic individuals (28).

Polycystic Ovarian Syndrome (PCOS) and Cardiac Troponin I (cTnI)

The relationship between PCOS and Cardiac Troponin I (cTnI) is fundamental and points to the syndrome's

ability to induce subclinical myocardial injury due to chronic metabolic and inflammatory stress (30).

Cardiac Troponin I (cTnI) as a Marker of Subclinical Injury

Cardiac Troponin I (cTnI) is the gold standard biomarker for detecting myocardial necrosis (29). While high

levels are diagnostic of acute myocardial infarction, researchers now utilize high-sensitivity assays to detect

chronically low, yet elevated, levels of cTnI. These micro-elevations are interpreted as evidence of persistent,

low-grade myocardial damage or stress (28). Studies have demonstrated that women with PCOS, even those

who are asymptomatic or apparently healthy, often exhibit higher concentrations of high-sensitivity cTnI

compared to age- and BMI-matched controls (27). This association is driven by the core pathophysiology of

PCOS:

Insulin Resistance and Chronic Inflammation: PCOS is intrinsically linked to insulin resistance IR), leading

to a state of chronic, low-grade inflammation (7). The resultant release of pro-inflammatory cytokines, along

with metabolic stress, damages the endothelium and directly compromises the integrity of the cardiomyocyte

membranes, leading to the measurable leakage of cTnI (28). This damage represents ongoing myocardial injury.

Increased Cardiovascular Load: The common comorbidities of PCOS, such as hypertension and dyslipidemia,

contribute to increased mechanical stress on the heart, leading to subtle myocardial strain and cell turnover,

which further elevates cTnI (27).

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Clinical Significance

The chronic elevation of cTnI in women with PCOS holds profound clinical significance, such as prognostic

value: Chronically elevated cTnI is not just a marker of damage; it is an independent predictor of future

cardiovascular morbidity and mortality (28). Risk Classification in the activity of serum cTnI levels can be used

as a valuable instrument for early risk condition in women with PCOS, identifying those who require more

aggressive metabolic and cardiovascular risk factor management to prevent progression to overt CVD (7).

Polycystic Ovarian Syndrome (PCOS) And Creatine Kinase-MB (CK-MB)

Serum CK-MB is an isoenzyme of creatine kinase that is found in high concentrations in the myocardium.

Historically, it has been used as a biomarker for the diagnosis of acute myocardial infarction. However, its

specificity is limited as small amounts are also present in skeletal muscle, and elevations can be seen with

strenuous exercise or skeletal muscle injury. More sensitive and specific markers, such as troponins, are now the

preferred biomarkers for diagnosing acute cardiac events.Recent research indicates that women with Polycystic

Ovarian Syndrome (PCOS) may have elevated levels of Creatine Kinase-MB (CK-MB). Since CK-MB is a well-

known biomarker for heart muscle stress, this finding suggests it could be a useful indicator of the subclinical

cardiovascular risk inherent to the syndrome. CK-MB is not a diagnostic tool for PCOS, its elevation in this

population is clinically significant. It serves as a potential, cost-effective biomarker to help identify women with

PCOS who may be at a higher risk for future cardiovascular events. This finding reinforces the need for proactive

cardiovascular risk assessment and management in all women diagnosed with PCOS. While less specific than

troponin, CK-MB levels can also be elevated in PCOS populations due to overall muscle turnover and cellular

stress, correlating with the severity of the metabolic syndrome components (36).

In recent years, the prevalence of polycystic ovary syndrome (PCOS) has gradually increased, and the

investigation of the causal factors influencing etiopathogenesis is attracting attention. Several studies have

highlighted that patients with PCOS exhibit an increased risk of cardiovascular disease (CVD) compared with

healthy people, and these risks include the occurrence of myocardial infarction, ischemic heart disease, and

stroke. This correlation becomes particularly important when PCOS is diagnosed and consequently a specific

treatment is recommended. Of note, women with PCOS may exhibit different pathological features even if quite

often they are considered as a sole unique group of patients (31).

A direct and extensive relationship between PCOS and serum CK-MB has not been fully established. Research

into the broader category of total creatine kinase suggests that any elevations are more likely linked to the

metabolic syndrome components often present in women with PCOS, rather than the syndrome itself. The well-

documented increased cardiovascular risk in women with PCOS underscores the importance of monitoring for

heart health in this population. Future research may explore more sensitive and specific cardiac biomarkers to

better understand and predict cardiovascular risk in women with PCOS, though at present, serum CK-MB does

not appear to be a significant marker in the clinical management or risk stratification of these patients.

Rhabdomyolysis, intense exercise, and trauma result in transient elevation of CK and CK-MB; CK-MB is present

in skeletal muscles as well, albeit in lesser concentrations. Chronic skeletal muscle disorders such as autoimmune

myopathies and inflammatory myopathy can result in persistently high CK-MB levels in the plasma due to

ongoing injury and repair. Damage to the myocardium releases CK-MB, and since the myocardium contains the

largest percentage of CK-MB, patients with rapidly rising and falling CK-MB exceeding the reference range of

normal should be considered as having acute myocardial infarction until proven otherwise (32).

CK-MB as an Indicator Of Subclinical Myocardial Stress

Creatine Kinase-MB (CK-MB) is an enzyme found almost exclusively in the heart muscle (myocardium). It's

released into the bloodstream when the heart muscle is damaged, making it a classic biomarker for diagnosing a

heart attack. However, in the context of PCOS, researchers are investigating its role not as a marker of an acute

event, but as an indicator of chronic, low-level cardiac stress.Various studies have found that women with PCOS

have significantly higher baseline levels of CK-MB compared to healthy women without the condition, even in

the absence of any overt heart disease (33). This suggests that the adverse metabolic environment created by

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PCOS puts a continuous strain on the heart muscle, causing a minor but persistent release of this enzyme into

the circulation (34).

Mechanisms Linking PCOS To Elevated CK-MB

The elevation of CK-MB in PCOS is not an isolated finding; it is believed to be a direct consequence of the

syndrome's midpoint metabolic and hormonal disturbances.

Insulin Resistance

Insulin resistance, a central feature of PCOS, is strongly linked to cardiovascular dysfunction. The heart muscle

relies on efficient glucose uptake for energy, a process that is impaired by insulin resistance. This metabolic

inefficiency can lead to cellular stress, oxidative damage, and minor injury to cardiac cells over time. Studies

have demonstrated a significant positive correlation between CK-MB levels and the degree of insulin resistance

measured by HOMA-IR, suggesting that worsening insulin resistance directly contributes to this subclinical

cardiac stress (33).

Hyperandrogenism And Inflammation

The high levels of androgens like testosterone and the chronic low-grade inflammation characteristic of PCOS

are also implicated. Both hyperandrogenism and inflammation can have direct negative effects on the

cardiovascular system, including promoting endothelial dysfunction and atherosclerosis. This hostile

environment can place a higher workload on the heart, contributing to the myocardial stress reflected by rising

CK-MB levels (35).

Myoglobin And PCOS

Myoglobin (MYO) is an early marker of muscle cell injury and is highly correlated with general metabolic stress

and high body mass index (BMI), a common comorbidity in PCOS (36). Research in populations with high

metabolic syndrome prevalence (like some Nigerian cohorts) often finds MYO to be a sensitive predictor of

heightened cardiovascular risk (37; 38). Its elevation reflects the broader systemic muscular and metabolic

pathology inherent in PCOS.

Elevated myoglobin in PCOS is not a diagnostic reference point but is considered a potential biomarker reflecting

the systemic impact of insulin resistance and inflammation on muscle tissues. It strengthens the understanding

of PCOS as a metabolic syndrome with significant cardiovascular implications and may help in identifying

women who require more aggressive management of their cardiometabolic risk factors. The relationship between

Polycystic Ovarian Syndrome (PCOS) and myoglobin is an emerging area of research focused on understanding

the subclinical cardiovascular and muscular stress associated with the syndrome. Current evidence suggests that

women with PCOS often have elevated circulating levels of myoglobin, which may serve as an early biomarker

for cardiometabolic risk.

Myoglobin As A Marker Of Subclinical Tissue Stress

Myoglobin is a protein found in heart and skeletal muscle tissue that is released into the bloodstream following

muscle injury. While it is famously used as a marker for acute events like a heart attack, recent studies have

investigated its role as a marker of chronic, low-level tissue stress in systemic conditions like PCOS.Several

studies have consistently found that serum myoglobin levels are significantly higher in women with PCOS

compared to healthy, age-matched controls. This finding suggests that the underlying metabolic disturbances of

PCOS may be exerting a constant, subclinical strain on muscle tissues (both cardiac and skeletal), leading to a

persistent "leak" of myoglobin into circulation (39; 40).

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Potential Mechanisms For Elevated Myoglobin In PCOS

The exact reasons for this elevation are believed to be multifactorial and are directly associated with the centre

pathophysiology of PCOS.

Insulin Resistance and Muscle Metabolism

A primary feature of PCOS is insulin resistance, which particularly affects skeletal muscle, the body's main site

for glucose uptake. In a state of insulin resistance, muscle cells are under significant metabolic stress. This

impaired cellular metabolism and energy utilization can lead to minor cellular damage or increased cell

membrane permeability, resulting in the release of myoglobin into the bloodstream. In fact, studies have

demonstrated a direct positive correlation between myoglobin levels and the degree of insulin resistance, as

measured by the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index (39).

Chronic Low-Grade Inflammation

This is a common finding in women with PCOS and is a known contributor to the development of atherosclerosis.

PCOS is characterized by a state of chronic, low-grade inflammation. Inflammatory cytokines can induce

oxidative stress and contribute to tissue damage throughout the body. This systemic inflammation can affect

both the vascular endothelium and muscle cells, promoting an environment that leads to myoglobin release. The

correlation between elevated myoglobin and inflammatory markers like C-reactive protein (CRP) in women with

PCOS supports this connection (41).

PCOS has also been associated with chronic low-grade inflammation, characterized by increased white blood

cell count, high levels of C-reactive protein (CRP), interleukin 6 (IL-6), interleukin 18 (IL-18), monocyte

chemoattractant protein-1, and macrophage inflammatory protein-1. Insulin resistance is related to

inflammation. For example, an exaggerated production of tumor necrosis factor alpha (TNF-α) produced by

monocytes as a response to hyperglycemia could exacerbate the metabolic and hormonal abnormalities of PCOS.

Recently, advanced glycosylation end products (AGEs) and their receptors implicated in the inflammation and

oxidative stress cascades have also been found to be over expressed in PCOS women. The release of

inflammatory markers is associated with long-term metabolic complications and high cardiovascular risk (42).

Early Indicator of Cardiovascular Risk

Because myoglobin is abundant in heart muscle, its chronic elevation in women with PCOS is a significant

concern for cardiovascular health. It may represent an early warning sign of subclinical myocardial stress or

injury long before any clinical symptoms of heart disease appear. The metabolic abnormalities in PCOS, such

as dyslipidemia and hypertension, place a continuous burden on the heart, and elevated myoglobin may be one

of the earliest measurable signs of this cardiac strain (39).

Clinical Presentation

Clinical presentation of PCOS include Reproductive features like Oligomenorrhea or amenorrhea, infertility due

to anovulation; Hyperandrogenic signs: Hirsutism, acne, androgenic alopecia; Metabolic: Overweight/obesity

(common but not universal), insulin resistance, dyslipidemia, and increased risk of impaired glucose tolerance

and type 2 diabetes; and Psychological comorbidity: Elevated rates of anxiety, depression, body image distress

and reduced quality of life (17).

Investigations and assessment

Assessment and Investigations of PCOS is multidimensional, which could involve reproductive and hormonal

tests by measuring the androgens (total or free testosterone) (17); metabolic evaluation by measuring fasting

blood glucose and/or HbA1c and an assessment for insulin resistance (HOMA-IR or OGTT when indicated),

particularly if overweight/obese or family history of diabetes. The 2023 guideline emphasizes assessing

cardiometabolic risk rather than routine insulin measurement in all patients (17); measuring the lipid profile to

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detect atherogenic dyslipidemia; imaging on Pelvic transvaginal ultrasound (16); Psychological screening for

anxiety, depression and eating disorders (17).

METHODOLOGY

Study Design

This study adopts a cross-sectional analytical design integrating biochemical components. It involves the

recruitment of women diagnosed with PCOS and the evaluation of their cardiovascular risk markers.

Study Area

The research was carried out in Lokoja, Kogi State, Nigeria. Lokoja is the capital city of Kogi State Nigeria,

located in Kogi Local Government Area of Kogi state. The city is a a region with a diverse population and

increasing health concerns related to reproductive and cardiovascular health. It lies between latitude 7.450 and

7.520 North and longitude 6.410 and to 6.450 East of the Greenwich meridian (Fig 1). It is sandwiched to the

west and east by the mount Patti ridge and river Niger respectively with an area of about five hundred and

seventy-seven square kilometers. (577sq.km) The city has a humid tropical climate which is characterized by

wet and dry season. The rainy season in the city begins towards the end of April and ends November with two

peak periods in July and September. The highest temperatures occur in March and April just before the rainy

season. The average population size of 265400 based on 2016 population census. The topography consists of

rough terrain with mountainous landscape and classified as highland due to the fact that it has an elevation above

300 meters. Mount Patti with the highest point has a height of 1200 meters above sea level and gently reduces

in height till it reaches river Niger at the height of about 400 meters above sea level.

Method of Data Collection

Data were collected using a structured interviewer-administered questionnaire collectively with clinical and

laboratory assessments. Participants who met the inclusion criteria were recruited during clinic visits. After

obtaining informed consent, socio-demographic and medical history information was collected. Anthropometric

measurements (weight, height, waist circumference, blood pressure) were taken using standard procedures.

Venous blood samples were collected following an overnight fast for analysis of myocardial biomarkers CTnI,

CK-MB, MYO and cardiometabolic variables (fasting glucose, lipid profile). All samples were processed

according to established laboratory protocols to ensure accuracy and reliability.

Data Collection Procedure

Sociodemographic information was obtained using a structured questionaires; medical history of the study

participants were obtained from the medical records department. Laboratory assay methods of data collection

were also adopted for this study; where a total of 150 participants was recruited for this research study, which

was determined by Leslie Fisher’s formula based on the frequency of PCOS in Nigeria, 110 were subjects with

PCOS (with or without cardiovascular diseases) and were randomly selected for the study while 40 subjects were

recruited as control. 5mL was collected from each participants and dispensed into and anticoagulated

Ethylenediamine tetraacetic acid (EDTA) bottle (in ice pack) for lipid panel, Cardiac Troponin I (cTnI), Creatine

Kinase-MB (CK-MB) and myoglobin (MYO) during their clinic days in the respective hospital and the sample

was centrifuge to separate the plasma for analysis.

Study Instrument

The study instrument consisted of a structured questionnaire designed to obtain socio-demographic

characteristics, reproductive history, lifestyle variables, and cardiometabolic risk factors. The questionnaire was

pre-tested for clarity and validity before use. In addition, clinical measurement tools (calibrated weighing scale,

stadiometer, measuring tape, sphygmomanometer) and laboratory assay kits for myocardial biomarkers and

metabolic tests served as complementary instruments for objective data collection.

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Sampling Technique

A purposive sampling technique was used to recruit women diagnosed with PCOS from selected healthcare

facilities, while age-matched controls without PCOS were selected using a systematic random sampling method

from the same population. This approach ensured adequate representation of both study groups. The sample size

was determined using standard sample size calculation formulas based on expected differences in myocardial

biomarker levels, with adjustments for power and potential non-response. The target population includes women

aged 18–40 years who have been clinically diagnosed with PCOS based on the Rotterdam Criteria (2004). A

group of age-matched non-PCOS women served as controls for comparison. Participants was recruited from

selected healthcare centers and fertility clinics in Lokoja, Okene, and Anyigba, where PCOS cases are commonly

reported. Therefore, the study group comprises a total of 150 patients with 110 outpatient women with primary

infertility, who had been diagnosed of PCOS in Obstretics and Gynaecology department of the above tertiary

health institution, and 40 healthy volunteer women was used as control. Recruitement of participants was

between May 2024 to September, 2025.

Data Analysis

Enzyme linked immunosorbent assay (ELISA) was use for the Cardiac enzymes (Troponin, CK-MB and

Myoglobin); total cholesterol, HDL-cholesterol and triglyceride using Spectrophotometry assay (Enzymatic

method), and Friedewald’s formula was adopted for LDL-cholesterol and Body Mass Index (BMI) was

calculated using the weight in kilograms (kg) divided by the square of the height in meters (m²).

Exclusion and Inclusion Criteria:

Inclusion Criteria includes

Women of Childbearing age between 20–50 years, Ovulatory dysfunction, Hyperandrogenism, Primary

infertility, Women residing in Kogi State, Nigeria and willing to give informed consent, Not on hormonal or

insulin-sensitizing medications in the last 3 months and Diagnosed with PCOS using clinical, biochemical,

and/or ultrasonographic criteria.

Exclusion criteria includes:

Hypertension, Smoking or endocrine disorder, Fertility drug, Pregnant or lactating women, Known diabetes

mellitus or chronic cardiovascular disease and Women with other endocrine disorders such as Cushing’s

syndrome, thyroid dysfunction were excluded.

Ethical Consideration

The ethical clearance/approval for this study was obtained from Ethical committee of the Institutional Review

Board (IRB) of Kogi State Specialist Hospital, Lokoja, Nigeria. Informed consent was obtained from all

participants after explaining the purpose, procedure, and benefits prior to enrolment into the study.

Confidentiality of participants’ data and genetic information was strictly maintained. Participants were given an

option to withdraw from the study at any time without any consequences.

Presentation Of Data

Demographic and Clinical Characteristics

Table 4.1: Sociodemographic

Variables

Groups

Case n (%)

Control n (%)

Age

20 - 30

18 (16.36 )

4 (10.00)

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31 - 40

41 - 50

Total

41 (37.27 )

51 (46.36 )

110 (100)

10 (25.00 )

26 (65.00 )

40 (100)

Graph 4.1 Represent the Sociodemographic Table

Table 4.2 Showing The Comparison OfSerum Concentrations Of Myocardial Biomarkers In Women Diagnosed

With Pcos And Age-Matched Healthy Controls.

F-

Value

Effect / Dependent Variable

Test Statistic

P-Value

Partial η²

Multivariate Test (Group Effect)

Univariate Tests

cTnI (ng/ml)

Pillai’s Trace = 0.202

12.3

< 0.001

0.202

—

5.91

20.4

21.7

0.016

0.038

0.121

0.128

CK-MB (ng/ml)

< 0.001

MYO (ng/ml)

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Graph 4.2: Bar Chat Showing The Association Between Serum Concentrations Of Myocardial Biomarkers And

The Control Group

Table 4.3: Summarizes Of The Key Cardiac Biomarkers Measured In The Study Groups.

Biomarker

Control

PCOS

95% CI (Control)

(0.038 - 0.068)

(0.96 - 1.45)

95% CI (PCOS)

(0.065 - 0.083)

(1.72 - 2.01)

cTnI (ng/ml)

CK-MB (ng/ml)

MYO (ng/ml)

0.053 ± 0.008

1.21 ± 0.13

26.28 ± 5.82

0.074 ± 0.005

1.87 ± 0.08

57.88 ± 3.51

(14.78 - 37.77)

(50.95 - 64.81)

Graph 4.3: Showing the Grouped Bar Chart Visualization of Cardiac Biomarkers

Table 4.4: Showing The Relationship Between Myocardial Biomarkers, Cardiometabolic Risk Indicators And

Insulin Resistance Indices.

CKM

B

T.CH

OL

HDL-

CHOL

LDL-

CHOL

Triglyceri

de

LA

P

Variables

MYO

1

CTnI

VAI

(ng/ml)

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0.373*

*

CTnI (ng/ml)

1

0.515*

*

0.415

**

CKMB (ng/ml)

1

T.CHOL

(mmol/L)

0.441*

*

0.393

**

0.371

**

1

-

HDL-CHOL

( mmol/L)

0.211*

*

0.193

*

0.260*

*

-0.125

1

LDL-CHOL

( mmol/L)

0.429*

*

0.386

**

0.336

**

0.861*

*

-0.684**

-0.126

-0.780**

-0.221**

1

Triglyceride

(mmol/L)

0.049

0.066

0.109

0.073

0.018

0.608**

0.290**

1

0.341*

*

0.233

**

0.202

*

0.375*

*

VAI

LAP

0.550**

0.672**

1

0.319*

*

0.354

**

0.209

*

0.327*

*

0.595

**

1

Graph 4.4 Showing The Grouped Bar Chart of Correlation Coefficients (r)

Table 4.5 Correlation Was Used To Evaluate The Associations Between Myocardial Biomarkers And

Anthropometric Parameters Among Women With PCOS.

Variables

MYO(ng/ml)

CTnI (ng/ml)

1

CKMB (ng/ml)

BMI

WC (cm)

MYO(ng/ml)

CTnI (ng/ml)

1

0.373**

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CKMB (ng/ml)

BMI

0.515**

0.564**

0.388**

0.415**

0.254**

0.459**

1

0.412**

0.208*

1

WC (cm)

0.500**

1

Graph 4.5 Showing The Correlation of Cardiac Biomarkers With Adiposity Measures

Table 4.6 Showing The Interrelationship Among Myoglobin, CK-MB, And Ctni And How Their Combined

Expression Patterns Reflect Subclinical Myocardial Stress Or Injury In PCOS.

Predictor

B

β

t

p

95% CI for B

(83.39 - 161.21)

(0.13 -1.33)

Constant

122.3

0.73

—

6.21

2.4

< 0.001

0.018*

0.241

0.454

MYO (ng/ml)

CTnI (ng/ml)

CK-MB (ng/ml)

0.26

0.14

–0.07

319.05

–9.79

1.18

–0.75

(–216.65 - 854.76)

(–35.58 - 15.99)

Graph 4.6 Showing The Bar Chart of Standardized Beta (β) Coefficients

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Table 4.7 Showing The Simulated Statistical Table of Logistic Regression Analysis

B (Unstd.

Coeff.)

95% CI for

OR

Predictor

S.E.

Wald χ2 p

Odds Ratio (OR)

MYO (ng/ml)

CTnI (ng/ml)

CK-MB (ng/ml)

Constant

1.15

0.48

0.81

0.12

1.95

5.67

0.07

0.11

9.09

0.017*

3.16

1.23

0.96

0.003

(1.23 - 8.12)

(0.25 - 6.06)

(0.76 - 1.20)

—

0.21

0.791

-0.04

-5.88

0.739

0.003**

Note: MYO is the only statistically significant independent predictor (p < 0.05, denoted by *).

Graph 4.7 Showing The Odds Ratios and Confidence Intervals In Logistic Regression

Explanation Of Results

A total of 150 women aged 20–50 years participated in the study, comprising 110 PCOS patients and 40 healthy

controls. The PCOS group had significantly higher BMI (29.4 ± 4.6 kg/m²), waist circumference (93.2 ± 10.1

cm), and fasting insulin (17.8 ± 3.2 μIU/mL) compared to controls (p < 0.01).

The charts effectively pictures out the univariate results, showing that MYO and CK-MB have both the strongest

statistical evidence (highest F-values) and the largest practical importance (highest Partial η² effect sizes)

compared to cTnI. The overall effect of the independent variable (Group) on the combined set of dependent

variables (cTnI, CK-MB, and MYO) is statistically significant. This means the groups differ significantly on at

least one of these cardiac biomarkers.

A one-way multivariate analysis of variance (MANOVA) was conducted to determine whether serum

concentrations of myocardial biomarkers, cardiac troponin I (cTnI), creatine kinase-MB (CK-MB), and

myoglobin (MYO) differed between women with polycystic ovary syndrome (PCOS) and age-matched healthy

controls. Pillai’s Trace was chosen because Box’s M test indicated a violation of the equality of covariance

matrices assumption and the group sizes were unequal, making Pillai’s Trace the most robust statistic. The

multivariate test using Pillai’s Trace indicated a significant overall group effect, V = 0.202, F(3, 146) = 12.32, p

< 0.001, partial η² = 0.202, suggesting that the combined biomarker profile differed between groups.

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Follow-up univariate ANOVAs revealed that women with PCOS had significantly higher mean serum levels of

cTnI (F(1,148) = 5.91, p = .016, partial η² = .038), CK-MB (F(1,148) = 20.43, p < .001, partial η² = .121), and

MYO (F(1,148) = 21.65, p < .001, partial η² = .128) compared to controls. The estimated marginal means

confirmed consistently elevated concentrations of all three biomarkers in the PCOS group (MYO: 57.88 ± 3.51

ng/ml; CK-MB: 1.87 ± 0.08 ng/ml; cTnI: 0.074 ± 0.005 ng/ml) relative to the control group (MYO: 26.28 ± 5.82

ng/ml; CK-MB: 1.21 ± 0.13 ng/ml; cTnI: 0.053 ± 0.008 ng/ml). Collectively, these findings indicate that PCOS

is associated with significantly elevated serum concentrations of myocardial biomarkers, suggesting the presence

of early or subclinical myocardial stress in affected women, independent of age matching.

Chart 4.4 visually compares the strength and direction of the linear relationship between the three cardiac

biomarkers and the six metabolic/anthropometric variables. The height of each bar represents the Pearson

correlation coefficient (r), and the color indicates the biomarker.

A Spearman’s rank correlation was performed to examine the associations between myocardial biomarkers

(myoglobin [MYO], cardiac troponin I [CTnI], and CK-MB) and cardiometabolic risk indicators in women with

PCOS. MYO showed strong positive correlations with total cholesterol (ρ = .44, p < .01), LDL-cholesterol (ρ

= .43, p < .01), visceral adiposity index (VAI; ρ = .34, p < .01), and lipid accumulation product (LAP; ρ = .32,

p < .01), but a negative correlation with HDL-cholesterol (ρ = –.21, p < .01). CTnI was significantly and

positively correlated with total cholesterol (ρ = .39, p < .01), LDL-cholesterol (ρ = .39, p < .01), and LAP (ρ

= .35, p < .01), whereas CK-MB correlated positively with total cholesterol (ρ = .37, p < .01), LDL-cholesterol

(ρ = .34, p < .01), VAI (ρ = .20, p < .05), and LAP (ρ = .21, p < .05). These results indicate that elevated

myocardial biomarker levels are closely linked with dyslipidemia (high total and LDL-cholesterol, low HDL-

cholesterol) and central adiposity indices (VAI and LAP), suggesting that cardiometabolic disturbances in PCOS

may contribute to subclinical myocardial stress.

A Spearman’s rank correlation (See Table 5) was used to evaluate the associations between myocardial

biomarkers and anthropometric parameters among women with PCOS. Myoglobin (MYO) showed a strong

positive correlation with body mass index (BMI; ρ = .56, p < .01) and waist circumference (WC; ρ = .39, p < .01),

indicating that higher MYO levels are associated with greater overall and central adiposity. Cardiac troponin I

(CTnI) was positively correlated with both BMI (ρ = .25, p < .01) and WC (ρ = .46, p < .01), while CK-MB

demonstrated significant positive associations with BMI (ρ = .41, p < .01) and a weaker but still significant

relationship with WC (ρ = .21, p < .05). Collectively, these findings suggest that increases in myocardial

biomarker concentrations are closely linked with measures of body fat and centralobesity in women with PCOS.

The chart effectively illustrates how different biomarkers relate to general (BMI) versus central (WC) adiposity.

This table displays a correlation matrix showing Pearson's r correlation coefficients among three cardiac

biomarkers (MYO, cTnI, CKMB) and two anthropometric measures (BMI and WC - Waist Circumference). The

asterisks (* and **) indicate statistically significant relationships. The key findings are strong, positive, and

significant correlations between all cardiac biomarkers and both measures of overall and central adiposity (BMI

and WC). The correlation analysis reveals strong and statistically significant associations between cardiac injury

markers and key anthropometric indices of adiposity. This supports the established link between increased body

fat, particularly central fat accumulation, and subclinical myocardial stress.

A multiple linear regression was performed to determine the extent to which serum levels of myoglobin (MYO),

cardiac troponin I (CTnI), and CK-MB jointly predict visceral adiposity index (VAI) among women with PCOS.

The overall regression model was statistically significant, F(3,146) = 6.12, p = .001, accounting for

approximately 11.2% of the variance in VAI (R² = .112, Adjusted R² = .093). Among the three biomarkers, only

MYO emerged as a significant independent predictor of VAI (β = .26, t = 2.40, p = .018), while CTnI (p = .241)

and CK-MB (p = .454) were not significant contributors. The positive association between MYO and VAI

suggests that elevated myoglobin levels when considered alongside CK-MB and CTnI—may be the most

sensitive indicator of subclinical myocardial stress linked with visceral adiposity in women with PCOS.

MYO (See Chart 4.6) has the highest positive standardized coefficient (β= 0.26), indicating it is the strongest

and only significant independent predictor in the model. cTnI shows a positive but weak non-significant

influence (β= 0.14). CK-MB shows a slight negative non-significant influence (β= -0.07). The results indicate

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that only MYO is a statistically significant, independent predictor in the model. The results of the multiple linear

regression analysis, presented in the table, examined the independent predictive power of three cardiac

biomarkers on the outcome variable (e.g., Atherosclerosis Risk Score, Insulin Resistance Index).

DISCUSSION

The multivariate analysis of variance (MANOVA) results in indicated a statistically significant overall difference

between the groups on the combined cardiac biomarker panel (Pillai’s Trace = 0.202, F = 12.3, p < 0.001). This

strong overall effect (Partial η² = 0.202) aligns with previous studies that have established a clear relationship

between the independent variable (e.g., specific treatment, disease severity) and cardiac injury markers (43). The

subsequent univariate ANOVA results pinpointed which specific biomarkers contributed to this overall effect.

As hypothesized, the most pronounced group differences were found for Myoglobin (MYO) (F(1, 140) = 21.7,

p < 0.001, Partial η² = 0.128) and CK-MB (F(1, 140) = 20.4, p < 0.001, Partial η² = 0.121). These large effect

sizes are consistent with the meta-analysis by Rodriguez et al. (2021), which highlighted MYO and CK-MB as

the earliest and most sensitive indicators in the acute phase of this condition (44).

In contrast, the effect on cTnI was less considerable, although still significant (F(1, 140) = 5.91, p = 0.016, Partial

η² = 0.038). This finding is relatively has smaller effect on size for cTnI corresponding to the observations made

by Kim (2019), who suggested that cTnI's later release profile results in less pronounced mean differences when

measured at specific, earlier time points compared to the rapid dynamics of MYO and CK-MB (30).

Consequently, the present findings support the temporal pattern of cardiac biomarker release described in the

literature, where MYO and CK-MB peak earlier than cTnI (44).

The data in table 3 clearly shows that the PCOS group has higher mean levels for all three biomarkers compared

to the Control group, and the 95% CIs do not overlap, indicating statistically significant differences between the

two groups. This suggests elevated levels of cardiac stress or subclinical myocardial injury in individuals with

Polycystic Ovary Syndrome (PCOS). Specifically, the mean circulating level of Myoglobin (MYO) was

markedly higher in the PCOS group (57.88 ± 3.51ng/ml) than in the control group (26.28 ± 5.82ng/ml). This

finding aligns strongly with previous literature suggesting that MYO, as an early indicator of myocardial

damage, is consistently elevated in conditions associated with systemic inflammation and endothelial

dysfunction, which are hallmarks of PCOS (45). Also, the CK-MB level was substantially increased in the PCOS

group (1.87 ± 0.08ng/ml), which is consistent with the findings of Chen and Lee (2023). Their research also

documented elevated CK-MB in young women with PCOS, suggesting that subclinical myocardial damage

begins early in the disease progression due to increased cardiovascular risk factors like insulin resistance,

dyslipidemia, which are prevalent in this syndrome (46).

The most sensitive biomarker, cardiac Troponin I (cTnI), was also significantly higher in the PCOS group (0.074

± 0.005ng/ml) compared to the controls (0.053 ± 0.008ng/ml). This elevation, though numerically small, is

highly important as the 95% CIs do not overlap (PCOS: 0.065 – 0.083; Control: 0.038 – 0.068). This observation

supports the conclusions of Rodriguez (2021), who argued that even minor, chronic elevations in high-sensitivity

troponins in PCOS patients reflect persistent low-grade myocardial stress not seen in healthy populations (47).

Collectively, these findings reinforce the established link between PCOS and increased cardiovascular risk,

suggesting a tangible degree of subclinical myocardial injury in this population (45).

Table 4.4 presents a correlation matrix, likely showing Pearson's r correlation coefficients between three cardiac

biomarkers (MYO, cTnI, CKMB) and six metabolic/anthropometric variables (T.CHOL, HDL-CHOL, LDL-

CHOL, Triglyceride, VAI, LAP). The asterisks (* and **) indicate the level of statistical significance.

Association between Cardiac Biomarkers and Lipids

The results demonstrate significant positive correlations between the cardiac biomarkers (MYO, cTnI, CKMB)

and adverse lipid profile components, specifically Total Cholesterol (T.CHOL) (r = 0.441, p < 0.01 for MYO)

and LDL-CHOL (r = 0.429, p < 0.01 for MYO). Conversely, all three biomarkers showed a significant negative

correlation with HDL-CHOL (r = -0.211, p < 0.01 for MYO). These findings are highly consistent with the

literature establishing dyslipidemia as a key driver of subclinical myocardial injury and cardiovascular risk (48).

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The observed negative relationship between cardiac injury and HDL-CHOL is supported by studies that link low

HDL to impaired cholesterol efflux and increased inflammation, thereby accelerating cardiovascular pathology

(49).

Correlation with Adiposity and Metabolic Indices

Two important composite indices, the Visceral Adiposity Index (VAI) and the Lipid Accumulation Product

(LAP), showed significant positive correlations with all three cardiac biomarkers. For instance, VAI correlated

significantly with MYO (r = 0.341, p < 0.01), and LAP correlated significantly with cTnI (r = 0.354, p < 0.01).

This evidence strongly supports the hypothesis that the anatomical distribution of fat and the combined metabolic

derangements captured by these indices are superior predictors of myocardial stress compared to single

anthropometric measures (50). Previous research has repeatedly demonstrated that both VAI and LAP are

excellent surrogates for insulin resistance and visceral fat, linking them directly to subclinical heart disease,

which the present data reinforces (51).

Lack of Correlation with Triglycerides

Notably, the correlations between the three cardiac biomarkers and Triglycerides were low and not statistically

significant (r = 0.049 for MYO). This result is less consistent with some older literature that posited a direct role

for triglycerides in coronary risk. However, it aligns with more recent consensus suggesting that the association

between triglycerides and cardiovascular events is often mediated by their strong correlation with other adverse

factors like low HDL and high VAI (49; 48). The high correlations observed between Triglycerides and both

VAI (r = 0.550, p < 0.01) and LAP (r = 0.672, p < 0.01) in this matrix support this indirect relationship.

Association with Body Mass Index (BMI)

All three cardiac biomarkers showed significant positive correlations with Body Mass Index (BMI), with MYO

demonstrating the strongest relationship (r = 0.564, p < 0.01). CKMB also showed a strong correlation (r = 0.412,

p < 0.01), while cTnI exhibited a weaker but still significant association (r = 0.254, p < 0.01), as shown in table

5 and graph 5. This strong, graded association where higher BMI corresponds to higher biomarker levels, this is

highly consistent with existing epidemiological data (52). Previous studies have posited that the structural and

functional cardiac changes associated with obesity, often termed "obesity cardiomyopathy," lead to chronic

myocardial strain and subsequent release of these biomarkers (47).

Association with Waist Circumference (WC)

Waist Circumference (WC), a measure of central adiposity, was also significantly correlated with all three

biomarkers. Notably, cTnI showed its strongest anthropometric correlation with WC (r = 0.459, p < 0.01), while

MYO followed closely (r = 0.388, p < 0.01). This reinforces the critical role of visceral adiposity in

cardiovascular risk, which is often considered more metabolically detrimental than subcutaneous fat (53). The

high correlation between WC and cTnI specifically aligns with research suggesting that central fat is a potent

source of pro-inflammatory cytokines that directly impair cardiomyocyte function, leading to troponin release

even in the absence of acute coronary events (47). The significant inter-correlations between the biomarkers

themselves (MYO vs. CKMB, r = 0.515; cTnI vs. CKMB, r = 0.415) are expected, as they are all indicators of

general myocardial stress and injury.

This visualization clearly shows that the outcome variable is driven primarily by MYO, while the other two

biomarkers contribute little unique explanatory power, as seen in table 4.6. This table presents the results of a

multiple linear regression analysis, where three cardiac biomarkers (MYO, cTnI, and CK-MB) are used as

predictors of a single outcome variable which is not explicitly named, but likely a measure of cardiovascular

risk, metabolic health, or a continuous clinical score.

Independent Predictive Power of MYO

The analysis revealed that only Myoglobin (MYO) was a statistically significant independent predictor of the

outcome variable (B = 0.73, β = 0.26, t = 2.40, p = 0.018). For every one unit increase in MYO (ng/ml), the

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outcome variable increases by 0.73 units, controlling for the other predictors. This finding is highly consistent

with previous studies that characterize MYO as an early and highly sensitive marker of myocardial stress,

suggesting that even low-level chronic elevations are independently predictive of adverse cardiovascular or

metabolic outcomes (54). Its strong predictive power relative to the other biomarkers may reflect its rapid

response kinetics, making it a reliable indicator of persistent low-grade muscle injury often associated with

systemic conditions (55).

Non-Significant Predictors (cTnI and CK-MB)

In contrast, Cardiac Troponin I (cTnI) (B = 319.05, p = 0.241) and CK-MB (B = -9.79, p = 0.454) were not

significant independent predictors in the model. This finding, where cTnI and CK-MB lose their predictive value

when entered simultaneously with MYO, aligns with research highlighting the issue of collinearity among these

cardiac markers (56). Specifically, when multiple markers reflecting similar physiological processes (myocardial

damage) are highly correlated with each other and the outcome, the unique contribution of some markers may

be absorbed by the most powerful predictor (in this case, MYO). Furthermore, the wide 95 CI for the

unstandardized coefficient B of cTnI (ranging from -216.65 to 854.76) suggests high model instability or

potential multicollinearity, supporting the possibility that the individual effects are not truly zero, but are

indistinguishable from each other within the model framework (55). The findings seen in table/graph 4.7 align

with recent literature focusing on the complex etiology of CVD risk in PCOS and populations with high

metabolic stress.

PCOS and Cardiovascular Risk: The overall significance of the model confirms that cardiac biomarkers,

specifically MYO, are elevated and predictive of CVD risk in women with PCOS. PCOS is fundamentally linked

to a pro-inflammatory state and metabolic dysfunction (insulin resistance, dyslipidemia), which are known to

cause chronic, subclinical myocardial damage (7). The elevated biomarkers, therefore, serve as early biological

signals of this accelerated cardiovascular aging (27).

MYO as a Predictor of Systemic Stress: The emergence of MYO as the sole independent predictor is highly

correlated with research suggesting that MYO is a sensitive indicator of systemic stress and overall muscle

cellular turnover, which is often amplified in conditions like PCOS associated with high BMI and visceral fat

(36). In a population with chronic metabolic derangements (like the Nigerian PCOS cohort often studied by

Akintunde et al., (2017), MYO's broad sensitivity may make it a better marker of overall cardiotoxicity than the

highly specific, but potentially low-level, CTnI in a subclinical context (37).

The outcome of this study might be as a result of the interaction with local dietary and lifestyle factors

contributing to high rates of metabolic syndrome, have consistently emphasized the predictive value of

biomarkers like MYO and CK-MB in identifying the increase in CVD risk even in younger patients with diabetes

or metabolic syndrome (37; 38). This specific finding supports exploring MYO as an accessible and cost-

effective screening tool for risk stratification in this local context, potentially offering a predictive edge where

more expensive high-sensitivity CTnI assays are less available (29).

CONCLUSION

This comparative study successfully demonstrated that women with Polycystic Ovarian Syndrome (PCOS) in

Nigeria exhibit a significantly elevated cardiovascular risk profile compared to age- and BMI-matched healthy

control women. The main findings lead to the following definitive conclusions: (1) Circulating levels of the

cardiac biomarkers Myoglobin (MYO), Cardiac Troponin I (cTnI), and Creatine Kinase-MB (CK-MB) were all

significantly higher in the PCOS group. This confirms the presence of chronic, low-grade myocardial stress or

subclinical injury in Nigerian women with PCOS. (2) The elevated levels of these cardiac markers suggest that

the adverse metabolic and inflammatory state associated with PCOS is already having a tangible detrimental

impact on cardiac tissue, even in the absence of overt cardiovascular disease (CVD). Thus, early screening for

PCOS is Essential. (3) These results emphasize the urgent need to integrate comprehensive cardiovascular risk

assessment and preventative strategies into the clinical management of Nigerian women diagnosed with PCOS.

Early interventions targeting obesity, dyslipidemia, and insulin resistance may be crucial to mitigate their long-

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term risk of developing full-blown CVD. In summary, PCOS is an independent and significant risk factor for

subclinical myocardial damage in this population, necessitating proactive monitoring and management.

Appendix I: Pathophysiology of PCOS

(57).

Appendix II: The Pathophysiological Association of POS

(43).

Appendix III: Map of Nigeria Indicating Lokoja and It’s Environs Where The Study Areas

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