1,3,4,5,6 Department of Pharmacy Practice, Swamy Vivekanandha College of Pharmacy
2 Swamy Vivekanandha Medical Care Hospital and Research Institute
Polycystic ovarian syndrome (PCOS) is a multifactorial endocrine disorder characterized by significant clinical and metabolic variability, which often results in a delayed diagnosis and insufficient therapy. With an emphasis on hormonal, metabolic, inflammatory, genetic, proteomic, metabolomic, and microbiome-based markers that provide better diagnostic sensitivity and specificity over traditional standards, this comprehensive analysis covers recent advancements in PCOS biomarkers and diagnostic methods. The study highlights challenges caused by phenotypic overlap and test variability while critically analyzing the limitations of the Rotterdam and NIH criteria, among other diagnostic standards now in use. Innovations in imaging (including radiomics) and artificial intelligence and machine learning are being explored as ways to improve phenotypic classification and offer customized treatment. The clinical utility and validation of candidate biomarkers are looked at in terms of how well they can direct risk assessment, early intervention, and management plans tailored to individual populations. Future objectives include standardized biomarker panels, integration of digital health and multi-omics technologies, and robust cohort-based validation to advance the precision medicine paradigm in PCOS diagnosis and therapy.
PCOS is the most prevalent endocrine-metabolic disorder affecting women of reproductive age; its prevalence is estimated to be between 6 and 13% worldwide, but approximately 70% of cases remain untreated. PCOS was first identified by Stein and Leventhal in 1935 and is characterized by polycystic ovarian morphology, hyperandrogenism, and chronic anovulation. The symptoms of PCOS vary greatly between individuals and ethnic groups.[1] PCOS is essentially the consequence of a complex interplay between hormone imbalance, metabolic dysfunction, and hereditary vulnerability. Hyperandrogenism and insulin resistance are the two primary factors affecting the metabolic and clinical phenotype. Elevated circulating androgens cause hirsutism, acne, and ovulatory failure, while insulin resistance causes hyperinsulinemia, which increases ovarian androgen production and decreases hepatic synthesis of sex hormone-binding globulin.[2] Beyond reproductive failure, the illness affects various bodily components. Women with PCOS are more likely to have metabolic syndrome, type 2 diabetes, obesity, endometrial cancer, and cardiovascular disease. Psychological comorbidities like anxiety, depression, and negative body image are becoming increasingly recognized as part of its burden.[3] Despite decades of research, the precise cause of PCOS remains unknown. The available findings suggest a complicated hypothesis that includes endocrine disruption, intrauterine environmental variables, genetic susceptibility, and dysbiosis of the gut microbiota. These factors combine to upset the hypothalamic-pituitary-ovarian axis and metabolic balance, which causes the characteristic symptoms of PCOS. [4] Due to its chronic and varied character, early detection and treatment are critical to preventing long-term issues. While altering one's lifestyle remains the cornerstone of therapy, advancements in biomarker identification, omics, and artificial intelligence may enhance the accuracy of diagnoses and customize treatment regimens. [5]
2. Pathophysiology of PCOS
Fundamentally, polycystic ovarian syndrome (PCOS) is a multifactorial endocrine and metabolic illness that results from the intricate interaction of environmental, neuroendocrine, genetic, epigenetic, and metabolic factors. PCOS develops by a network of interrelated mechanisms that sustain hormonal imbalances and reproductive dysfunction rather than a single causal process.[6]
2.1 Genetic and Epigenetic Foundation
Genetic and epigenetic changes passed down through family history are the basis of PCOS vulnerability. Genes controlling important metabolic processes, ovarian steroidogenic function, and androgen production pathways are altered in women with genetic susceptibility. The family clustering of PCOS and the varied severity among afflicted individuals can be explained by these inherited differences, which establish an underlying vulnerability to developing the disease when exposed to triggering environmental factors.[6]
2.2 Neuroendocrine Dysregulation
A basic disturbance of the hypothalamic-pituitary-ovarian (HPO) axis, marked by aberrant patterns of Gonadotropin-Releasing Hormone (GnRH) secretion, is central to the pathophysiology of PCOS. Luteinizing hormone (LH) is disproportionately raised compared to follicle stimulating hormone (FSH) in women with PCOS due to increased hypothalamic GnRH pulse frequency. A cascade is created by this changed LH/FSH ratio: increased LH preferentially increases the production of excess androgens, especially testosterone and androstenedione, by ovarian theca cells. The negative feedback mechanisms that typically control gonadotropin secretion through progesterone and estradiol signaling are suppressed by high androgen levels. This creates a self-sustaining loop in which the loss of normal progesterone feedback keeps gonadotropin production elevated.[7]
2.3 Insulin Resistance and Hyperinsulinemia
Even in lean phenotypes, up to 70% of women with PCOS have insulin resistance. The ensuing hyperinsulinemia sets off a series of metabolic disorders that impact many systems. The main androgen transporter protein, Sex Hormone-Binding Globulin (SHBG), is suppressed in the liver by increased insulin. The percentage of free, or physiologically active, androgens rises significantly when SHBG availability is decreased, aggravating symptoms like acne and hirsutism. Insulin and insulin-like growth factor (IGF) signaling directly disrupt granulosa cell function and follicle development within the ovary, leading to follicle arrest at early developmental stages and the distinctive polycystic ovarian morphology with numerous immature follicles and no ovulation.[8]
2.4 Ovarian and Adrenal Steroidogenesis
In the ovarian component, the expression of steroidogenic enzymes in theca cells is specifically altered. These cells have elevated steroidogenic enzyme activity, especially those related to early androgen production, and become hyperresponsive to LH stimulation. This causes theca cells to produce an excessive amount of androgens, and the aberrant hormonal environment affects granulosa cell function, which stops normal follicle development and causes an accumulation of undeveloped follicles. Further contributing to systemic hyperandrogenism is the adrenal glands' increased production of dehydroepiandrosterone sulfate (DHEA-S), an adrenal androgen that peripherally transforms into stronger androgens.[9]
2.5 Chronic Inflammation and Oxidative Stress
Beyond its reproductive abnormalities, PCOS exhibits systemic inflammatory characteristics. Even in thin individuals, most women with PCOS have low-grade chronic inflammation, which suggests an innate inflammatory component. Elevated circulating markers such as C-Reactive Protein (CRP), TNF-α (tumor necrosis factor-alpha), and Interleukin-6 (IL-6) are indicative of this. Elevated markers and modified antioxidant defense mechanisms are indicators of increased oxidative stress that accompany this. These processes exacerbate insulin resistance and harm reproductive organs. Furthermore, women with PCOS exhibit different adipokine profiles, with raised leptin (pro-inflammatory) and decreased adiponectin (anti-inflammatory, insulin-sensitizing), creating a vicious cycle of metabolic dysfunction. .[9]
2.6 Gut Microbiota Dysbiosis
According to recent study, the pathophysiology of PCOS is influenced by dysbiosis of the gut microbiota. Microbiome composition is changed and microbial diversity is decreased in women with PCOS. A dysbiotic microbiota compromises the integrity of the intestinal barrier, increases the transfer of bacterial lipopolysaccharides, and causes systemic inflammation, among other pathophysiologic features. The production of short-chain fatty acids, especially butyrate, which promote barrier integrity and have anti-inflammatory properties, is decreased by the changed microbiota. Additionally, dysbiotic patterns are linked to decreased production of metabolites that improve insulin sensitivity and increased production of metabolites that promote insulin resistance. They are also less effective at metabolizing estrogens, which affects circulating estrogen levels. [10]
2.7 Integrated System Understanding
PCOS pathophysiology is a complex system in which no single mechanism functions independently. Vulnerability is caused by genetic predisposition; hormonal imbalances are caused by neuroendocrine dysregulation; insulin resistance increases the availability of androgens; excess androgens are produced by ovarian and adrenal steroidogenesis; tissues are damaged by oxidative stress and chronic inflammation; and dysbiotic microbiota worsen endocrine and metabolic disorders. The clinical variety of PCOS can be explained by these pathways, which operate in continuous feedback loops. Different women exhibit variable contributions from each pathway, leading to distinct phenotypic presentations of the underlying disease. [10]
Despite established diagnostic standards, the diagnosis of polycystic ovarian syndrome (PCOS) is still unclear and controversial. The underlying problem is caused by the condition's inherent heterogeneity, non-specific biochemical biomarkers, and overlapping clinical symptoms. Even with commonly used diagnostic standards like the Rotterdam Criteria (2003), which call for two of three characteristics (polycystic ovarian morphology, ovulatory dysfunction, and hyperandrogenism), clinicians still have a lot of trouble making accurate diagnoses in a variety of populations.[11]
3.1 Variability of Diagnostic Standards
Significant diagnostic confusion has been brought about by the spread of diagnostic criteria systems. Ovarian morphology is not included in the NIH criteria (1990), which puts ovarian dysfunction and hyperandrogenism at risk of underdiagnosis. Ovarian morphology was included in the Rotterdam criteria (2003), which loosened strictness by needing only two of three characteristics. However, this often led to an overdiagnosis of minor manifestations. Further changes were made in the 2018 International Guidelines and the Androgen Excess-PCOS Society (AE-PCOS) criteria (2006). Depending on the paradigm used, this variability yields radically different prevalence estimates, ranging from roughly 6% to over 20%. These discrepancies make it more difficult to manage patients, make cross-population study comparisons more complex, and make it more difficult to evaluate results on the prevalence, pathogenesis, and treatment effects of PCOS.[12]
3.2 Biochemical Marker Limitations
A. Androgen Measurements:
Dehydroepiandrosterone sulfate (DHEAS), free testosterone index, and total testosterone values are used in the biochemical evaluation of hyperandrogenism. However, these measurements show significant assay-to-assay variability and limited inter-laboratory repeatability, which means that the same blood sample examined in various labs may produce significantly different results. Although liquid chromatography–mass spectrometry (LC–MS/MS) is the gold standard and offers higher accuracy, its high cost and limited availability limit its application to specialist centers. Instead of utilizing biologically meaningful thresholds, the majority of clinical laboratories continue to use immunoassay techniques with acknowledged limitations, resulting in uneven classification based on arbitrary laboratory-specific reference ranges.[13]
B. Anti-Müllerian Hormone (AMH):
AMH is elevated in PCOS and is correlated with follicular excess, which is a measure of the number of tiny antral follicles. However, a number of factors prevent AMH from being used as a stand-alone diagnostic marker: substantial variation based on assay platform and device design; population heterogeneity with significantly different AMH reference ranges across ethnic and geographic populations; and assay calibration variations between manufacturers complicating the establishment of a universal threshold. International guidelines specifically advise against using AMH as a stand-alone diagnostic test, especially in teenagers whose AMH levels naturally fluctuate significantly during puberty and the early stages of reproduction.[14]
C. Luteinizing Hormone to Follicle Stimulating Hormone (LH/FSH) Ratio:
In clinical practice, this marker has shown to be unreliable despite its historical potential for diagnosis. Hormone levels vary significantly throughout menstrual cycles; gonadotropin secretion is intrinsically pulsatile, with rapid fluctuations occurring over minutes to hours; and the ratio shows significantly decreased sensitivity in obese and insulin-resistant women—groups that comprise significant proportions of women with PCOS. Because of this, the LH/FSH ratio has lost favor and is no longer advised by important diagnostic standards.[11]
4. Ultrasound-Based Diagnostic Limitations
4.1 Polycystic Ovarian Morphology (PCOM) Criteria:
A diagnostic criterion of 12 or more follicles per ovary was established under the original Rotterdam criteria. However, these initial thresholds are no longer relevant due to advancements in ultrasonic technology with higher-resolution transducers; more follicles can be seen with modern equipment than with earlier models, making direct comparisons across decades of research more difficult. Ovarian volume ≥10 cm³ and/or ≥20 follicles per ovary are recommended by current guidelines, but these limits are not universally validated. Diagnostic accuracy is influenced by a number of technical factors, including patient-related factors like body habitus and ovarian accessibility, operator skill and experience (manual follicle counting is subjective and prone to inter-observer variability), and transducer frequency (higher frequency offers better resolution but reduced depth). In borderline circumstances, this variability adds significant diagnostic uncertainty.[11]
4.2 Age and Ethnicity Variability:
Ultrasound appearance of ovaries varies substantially based on reproductive age and ethnic background. There is a danger of overdiagnosis because adolescents often exhibit temporary polycystic ovarian morphology, which may resolve on its own throughout maturation. On the other hand, despite ongoing endocrine problems, diagnostic ovarian features vanish in perimenopausal women due to gradual follicle loss. Ethnic and population differences substantially affect PCOM characteristics; ovarian volume, follicle number, and morphologic features differ between ethnic groups, suggesting diagnostic thresholds developed in one population may be inappropriate when applied to others.[15]
4.3 Acceptability and Accessibility:
Specialized equipment and highly skilled personnel are needed for high-resolution transvaginal ultrasonography. In societies where transvaginal inspection is socially stigmatized, this procedure may be considered intrusive or culturally inappropriate for specific populations, such as teenagers and young women without children. Due to these practical obstacles, diagnostic ultrasound is not as widely available as it could be, forcing medical professionals to use transabdominal ultrasound, which produces lower-quality images, or to proceed without the necessary morphologic assessment.[16]
5. Diagnostic Ambiguity in Specific Populations
5.1 Adolescents:
Adolescents often exhibit PCOS-like clinical and biochemical characteristics, such as hirsutism, irregular menstruation, acne, and multifollicular ovaries, which are more typically associated with normal pubertal development than pathologic PCOS. There is a significant risk of overdiagnosis, which can have serious repercussions like psychological effects and needless medical procedures. International standards acknowledge that some adolescents with apparent PCOS-like symptoms spontaneously normalize throughout the transition to reproductive maturity, and therefore propose diagnoses only when persistent abnormalities are established and at least two years after menarche.[16]
5.2 Perimenopausal Women:
Underdiagnosis is the opposite diagnostic issue that perimenopausal women deal with. Even in women with long-term PCOS exhibiting endocrine problems, progressive follicle depletion results in a reduction of polycystic ovarian morphology on ultrasonography. Women are diagnosed with "no PCOS" despite ongoing metabolic and hormonal abnormalities since the Rotterdam criteria cannot be applied when diagnostic ovarian morphology disappears.[14]
6. Absence of Age- and Ethnically-Specific Reference Guidelines
The absence of regionally established diagnostic thresholds that take population differences in body composition, androgen metabolism, and ovarian shape into account represents a significant diagnostic gap. When compared to women of European heritage, South Asian women often exhibit severe metabolic abnormalities (such as insulin resistance, dyslipidemia, and elevated cardiometabolic risk) at significantly lower body mass indices. This metabolic variation raises the possibility that diagnostic criteria created for Western populations may not be suitable for other ethnic groups. The current dependence on Western-centric datasets restricts the applicability of criteria to a variety of groups across the globe, increasing the risk of both overdiagnosis and underdiagnosis in other populations. Large, varied prospective cohort studies are necessary to develop population-specific guidelines; this significant investment has not yet been made.[14]
7. Lack of Single Universal Biomarker
PCOS is still essentially an exclusionary diagnosis based on composite clinical and biochemical standards rather than a unique, pathognomonic molecular signature, in contrast to certain endocrine disorders with distinctive molecular signatures or single diagnostic biomarkers (such as thyroid-stimulating hormone for thyroid disease). Early diagnosis and appropriate risk assessment are significantly delayed by its absence. Despite having symptoms, women frequently go years without a diagnosis; by then, metabolic abnormalities and reproductive dysfunction have significantly worsened.[17]
Multi-biomarker panels that combine imaging data, metabolic markers (such as lipids, glucose tolerance, and inflammatory cytokines), and hormone assessments show promise, according to recent research. In order to better capture the complex nature of PCOS, these integrated techniques seek to provide comprehensive diagnostic markers. They suggest possible future avenues for enhancing diagnostics by shifting from straightforward single-marker techniques to integrated risk assessment strategies that take biological complexity into account, even though they are currently undergoing validation.[18]
8. Discordance Between Diagnostic Criteria and Cardiometabolic Risk
The low association between existing PCOS diagnostic criteria and cardiometabolic risk—the real causes of long-term morbidity and mortality—is an important but overlooked constraint. Insulin resistance, dyslipidemia, endothelial dysfunction, and cardiovascular disease are among the conditions that cause the most serious health effects in PCOS, and conventional diagnostic markers like AMH levels and ultrasound morphology do not accurately predict these conditions. While a woman with limited ovarian findings may have severe insulin resistance and significant cardiometabolic risk, a woman with textbook polycystic ovarian morphology may exhibit great metabolic health. Due to this discrepancy, systemic metabolic abnormalities that pose the most risks to long-term health consequences are not included in the current diagnostic criteria, which successfully screen for reproductive phenotype.[19]
As a result, reproductive traits like anovulation and hyperandrogenism continue to receive a disproportionate amount of diagnostic attention, whereas systemic cardiometabolic risks are frequently ignored. Opportunities to reduce cardiovascular risk may be lost if a woman with PCOS is diagnosed based on reproductive criteria and does not receive the proper metabolic test and care. A paradigm change toward more metabolically-informed diagnostic and risk stratification techniques is imperative in view of this fundamental discrepancy between diagnostic criteria and therapeutic outcomes.[19]
9. Emerging Hormonal Biomarkers in PCOS
The diagnostic limitations of conventional markers such as total testosterone, luteinizing hormone (LH), and FSH have prompted research into a range of novel endocrine biomarkers that more properly reflect the underlying pathophysiology of Polycystic Ovary Syndrome (PCOS). Increased sensitivity and phenotypic differentiation are provided by hormones that regulate folliculogenesis, gonadotropin signaling, and metabolic processes, according to new research. [20]
s the most widely validated hormonal biomarker for PCOS, AMH is secreted by the granulosa cells of pre-antral and small antral follicles. Since there are more early-stage follicles and follicle development is arrested in PCOS, the amount of AMH is two to three times higher than in healthy women.[21] Mechanistically, AMH interferes with FSH-dependent follicular expansion and stimulates LH-driven androgen production, which leads to follicular halt. Serum AMH levels are a surrogate diagnostic indication that is strongly correlated with antral follicle count (AFC) and polycystic ovarian morphology (PCOM).[22] Nevertheless, it is still challenging to reach a consensus on diagnosis because cutoff values (typically 4–6 ng/mL) vary based on ovarian reserve, age, ethnicity, BMI, and assay method. AMH criteria should be adjusted for age and ethnicity in order to increase sensitivity and reduce the need for invasive imaging, according to recent proposals.[23]
9.2 Kisspeptin
The KISS1 gene encodes the neuropeptide kisspeptin, which controls the hypothalamic-pituitary-gonadal (HPG) axis by activating GnRH neurons and affecting the release of LH and FSH.[24] Research indicates that women with PCOS have significantly greater levels of kisspeptin, which is linked to increased leptin, elevated LH, and hyperandrogenism. This suggests that abnormal GnRH pulse frequency, a characteristic of neuroendocrine dysfunction in PCOS, may be brought on by hyperstimulation of kisspeptin.[25] Results from various research are still inconsistent, despite positive links; some exhibit negative associations based on phenotype and cohorts with BMI controls. Nonetheless, kisspeptin exhibits potential as a biomarker for diagnosis and treatment, particularly in anticipating ovulatory failure and reaction to assisted reproduction. [26]
The hormones Inhibin A (INH-A) and Inhibin B (INH-B), which control FSH secretion and represent follicular function and selection, are produced by the pituitary levegranulosa cells. Increased INH-A levels are linked to hyperandrogenism and follicular excess in PCOS, in line with AMH and LH levels. Combination testing of AMH and INH-A increases diagnostic specificity and sensitivity in adolescent PCOS instances where ultrasound-based diagnoses are few. In one study, ideal cutoffs of AMH >5.8 ng/mL and INH-A >9.3 pg/mL were established, with corresponding combined sensitivity and specificity of 74% and 88%. INH-B, a marker of early follicular development, may be used to further differentiate reproductive outcomes and the severity of ovarian malfunction.[27]
Which is a sign of androgen synthesis and steroidogenic activity. Although it is still high in a large number of PCOS patients, it does not consistently correlate with either clinical hyperandrogenism or metabolic markers. Although it might supplement androgen indices for phenotypic characterisation, the available data restricts its usage as a stand-alone marker.[28]
The C-terminal part of the vasopressin prohormone, copeptin, is an indicator of metabolic stress and insulin sensitivity. Increased LH, insulin resistance, and cardiometabolic risk in PCOS have all been associated with elevated copeptin, a dual endocrine-metabolic biomarker.[29] Zinc-α2-glycoprotein (ZAG), chemerin, and adiponectin are examples of adipokines that show different expression patterns in connection to androgen status and metabolic phenotype.[30]
9.6 New Endocrine Substances: LTA4H, FGFBP1, and METRNL
Recent proteomic and endocrine panels have shown that FGFBP1 (Fibroblast Growth Factor Binding Protein-1), METRNL (Meteorin-like protein), and LTA4H (Leukotriene A4 Hydrolase) are promising diagnostic biomarkers irrespective of phenotype. In 31 These indicators outperformed traditional androgens in their capacity to distinguish PCOS from controls, with AUC values >0.9 across reproductive age groups and phenotypes. The combined diagnostic accuracy of FGFBP1/METRNL and LTA4H/METRNL is approximately 99%.[31]
10. Metabolic and Inflammatory Biomarkers in PCOS
It is becoming more widely acknowledged that PCOS is a systemic illness marked by broad metabolic abnormalities and persistent low-grade inflammation, going well beyond reproductive failure. Incorporating biomarkers that represent inflammatory status and metabolic dysfunction improves predictive ability and diagnostic accuracy significantly while also offering important insights into the underlying pathophysiological mechanisms behind PCOS symptoms.[17]
Metabolic Biomarkers
10.1 Insulin and Insulin Resistance Markers
One of the most common metabolic disorders is insulin resistance (IR), which affects 50–70% of women with PCOS. Increased circulating insulin disrupts normal glucose metabolism, raises hepatic VLDL production, inhibits the synthesis of Sex Hormone-Binding Globulin (SHBG), and—most importantly—stimulates ovarian theca cells to produce more androgens. The severity of insulin resistance is measured by several indicators. The degree of tissue insulin resistance is correlated with fasting insulin levels, which represent basal pancreatic insulin output. To evaluate hepatic insulin resistance, the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) calculates an index that combines fasting insulin and glucose.An alternate measure of pancreatic beta cell function is provided by C-peptide, an equimolar consequence of insulin secretion that more accurately reflects endogenous insulin synthesis than serum insulin.Crucially, increased androgenicity and metabolic issues in PCOS are strongly linked to raised insulin levels. Higher levels of circulating androgens, more severe reproductive dysfunction, and increased metabolic risk are all seen in women with higher levels of insulin resistance. Therefore, evaluating insulin resistance markers provide crucial information about the severity of metabolic dysfunction and aids in predicting the likelihood of reproductive dysfunction as well as the degree of cardiometabolic risk.[32]
10.2 Dyslipidemia and Lipid Biomarkers
Women with PCOS have typical dyslipidemic patterns, such as increased apolipoprotein B (ApoB) concentrations, decreased HDL cholesterol (HDL-C), and raised triglycerides (TG), which significantly increase the risk of atherosclerotic cardiovascular disease. These anomalies are indicative of atherogenic lipid patterns, which are marked by decreased anti-atherogenic HDL, increased VLDL particles, and enhanced tiny, dense LDL particles. Apolipoprotein-based ratios, especially the ApoB/ApoA1 ratio, offer better cardiovascular risk prediction than standard lipid measures. Apolipoprotein B provides more accurate cardiovascular risk assessment than LDL cholesterol alone because it represents the whole load of atherogenic particles regardless of cholesterol concentration. The ApoB/ApoA1 ratio provides better cardiovascular event prediction by comparing the load of atherogenic and antiatherogenic particles. These lipid biomarkers can be used to predict future cardiovascular events, quantify atherogenic risk, and identify women who need rigorous cholesterol-lowering treatments.[17]
10.3 Adipokines
Adipokines are secreted molecules from adipose tissue that regulate energy balance, glucose metabolism, inflammation, and reproductive function. In PCOS, dysregulation of adipose tissue leads to significant alterations in adipokine expression and circulating levels. Adipose tissue produces leptin in proportion to fat mass, which is increased in PCOS and has several detrimental effects. Reproductive dysfunction, such as anovulation and decreased fertility, the continuation of obesity, and the exacerbation of insulin resistance, is linked to elevated leptin. Leptin levels in PCOS are frequently disproportionately high for a given body weight, indicating "leptin resistance" in which target tissues show decreased leptin sensitivity and adipose tissue produces extra leptin, much like insulin resistance. PCOS is characterized by a decrease in adiponectin, an insulin-sensitizing and anti-inflammatory protein.Adiponectin has potent anti-inflammatory properties, improves muscle glucose use, and lowers hepatic glucose and VLDL synthesis. In PCOS, adiponectin decrease eliminates critical defense systems, permitting unchecked inflammatory and metabolic dysfunction. Insulin resistance, dyslipidemia, and cardiovascular risk are inversely correlated with adiponectin levels. Increased resistin in PCOS directly hinders insulin signaling and increases inflammation throughout the body. Similarly increased, chemerin acts as a pro-inflammatory chemokine that increases inflammatory responses and attracts immune cells while reducing insulin sensitivity. These changes in adipokines show how metabolic dysregulation in PCOS affects adipose tissue endocrine function as well, resulting in an inflammatory state of adipose tissue that sustains systemic metabolic and reproductive abnormalities.[33]
10.4 Fetuin-A
A liver-secreted glycoprotein called fetuin-A is elevated in PCOS and represents a new metabolic biomarker. Fetuin-A is a significant contributor to insulin resistance in PCOS because it directly prevents insulin receptor phosphorylation and hinders insulin signaling. The degree of insulin resistance, obesity severity, dyslipidemia, and systemic inflammation are all strongly correlated with elevated fetuin-A levels. Additionally, fetuin-A leads to the development of non-alcoholic fatty liver disease (NAFLD), a major comorbidity of PCOS, and is linked to increased hepatic steatosis. Fetuin-A offers additional prognostic information regarding the severity of metabolic dysfunction by acting as a biomarker of systemic insulin resistance and dysregulation of lipid metabolism.[34]
Inflammatory Biomarkers
10.5 High-Sensitivity C-Reactive Protein (hs-CRP)
A key component of the pathophysiology of PCOS is chronic low-grade systemic inflammation, which is linked to both cardiometabolic problems and reproductive abnormalities. PCOS is characterized by a considerably raised level of high-sensitivity C-reactive protein (hs-CRP), an acute phase protein mostly produced by hepatocytes in response to cytokine activation. This elevation persists even after adjusting for body mass index. The persistently high hs-CRP distinguishes PCOS as intrinsically inflammatory rather than merely obesity-consequential, highlighting inflammation's essential role in metabolic dysregulation. Significantly, hs-CRP levels in PCOS are correlated with several indicators of metabolic dysfunction, such as body mass index, dyslipidemia markers, insulin resistance severity (HOMA-IR), and cardiovascular risk factors. This association shows that metabolic failure and inflammation are related PCOS processes, with inflammatory activity both causing and sustaining metabolic disruption.[35]
10.6 Pro-Inflammatory Cytokines
PCOS is associated with high levels of certain pro-inflammatory cytokines that directly lead to pathophysiologic disorders affecting the metabolic and reproductive systems. Interleukin-6 (IL-6) is a key player in systemic inflammation and is consistently high in many PCOS groups. By increasing the hepatic synthesis of CRP, IL-6 amplifies the acute phase response and encourages the activation of systemic inflammation. IL-6 stimulates the synthesis of additional cytokines by immune cells, resulting in self-amplifying inflammatory cascades. Tumor Necrosis Factor-alpha (TNF-α) has several detrimental effects, including direct impairment of insulin signaling in skeletal muscle and adipose tissue, which exacerbates insulin resistance; stimulation of hepatic VLDL production, which contributes to dyslipidemia; and direct suppression of ovarian steroidogenesis, which may causing some cases of androgen insufficiency. Other pro-inflammatory cytokines that are high in PCOS include interleukin-1β (IL-1β), interleukin-8 (IL-8), and interleukin-18 (IL-18), all of which contribute to increased ovarian and systemic inflammation. IL-18 increases inflammatory responses while compromising immune control; IL-8 attracts neutrophils and inflammatory cells; and IL-1β activates inflammasomes, sustaining chronic inflammatory signaling. Chronic, multi-cytokine-mediated inflammation affecting reproductive organs, vascular endothelium, adipose tissue, pancreatic beta cells, and hepatic tissue is the result of these several increased pro-inflammatory cytokines.[36]
10.6 Vascular Endothelial Growth Factor (VEGF)
Vascular endothelial growth factor (VEGF) has a role in several pathologic processes that impact ovarian function and is significantly overexpressed in PCOS. Excessive VEGF production causes aberrant angiogenesis in theca interna and ovarian follicles, which is linked to hyperthecosis (excessive theca tissue development) and follicular arrest (cessation of normal follicle development). Normally, VEGF supports vascular development and angiogenesis. The aberrant vascular development impairs follicle growth in PCOS by upsetting the usual microenvironments necessary for granulosa cell development and oocyte maturation. Additionally, VEGF increases local inflammatory reactions by encouraging immune cell penetration into ovarian tissue.[36]
10.7 Adipokines as Inflammatory Mediators
As was previously mentioned, adipokines serve as both inflammatory cytokines and metabolic regulating hormones at the same time, demonstrating the relationship between inflammation and metabolic dysfunction in PCOS. Elevated leptin and resistin actively encourage inflammatory activation by promoting macrophage infiltration into adipose tissue and systemic pro-inflammatory cytokine production, but decreased adiponectin eliminates crucial anti-inflammatory protection. Adipokine dysregulation concurrently reduces insulin sensitivity and increases systemic inflammation, two essential PCOS pathologic processes that reinforce one another in self-amplifying cycles.[37]
Diagnostic and Clinical Applications:
Early Metabolic and Cardiometabolic Risk Identification Insulin, adipokines, and lipid markers are examples of metabolic biomarkers that allow for early intervention by objectively measuring the severity of insulin resistance and the cardiometabolic risk burden in individual women. Clinicians can identify women who are particularly at risk for type 2 diabetes mellitus, cardiovascular disease, and the progression of metabolic problems by including metabolic biomarker assessment rather than depending just on clinical features or traditional reproductive biomarkers. Women who have severe insulin resistance as determined by biomarker assessment may benefit from early pharmacologic treatment with insulin-sensitizing agents or intensive lifestyle interventions. Women who need extensive dyslipidemia care and cardiovascular risk factor modification can be identified with the use of lipid profiles and adipokine assessments.[37]
Inflammatory Status as Outcome Predictor
Chronic inflammation is indicated by inflammatory markers including hs-CRP and IL-6, which have also been shown to be predictive of poor cardiovascular and reproductive outcomes in PCOS. Increased levels of inflammatory markers are associated with a higher incidence of metabolic syndrome, correlate with the presence of subclinical atherosclerosis on imaging, and predict a higher risk of cardiovascular events. Elevated inflammatory markers are associated with lower fertility and worse results from fertility treatments in terms of reproductive outcomes. Therefore, measuring inflammatory biomarkers helps stratify women into risk categories that require more intense therapies by providing predictive information beyond what reproductive or conventional metabolic markers alone can.[35]
Personalized Methods and Improved Phenotypic Classification The use of inflammatory and metabolic indicators into multi-dimensional diagnostic panels has made it possible to classify PCOS phenotypes in a more advanced manner. Modern techniques acknowledge condition variability and categorize women into more precise phenotypic groups based on main pathophysiologic traits, as opposed to merely classifying women as having or not having PCOS based on old criteria. While some women have significant metabolic failure with relatively moderate reproductive characteristics, others may have primarily reproductive dysfunction with minimal metabolic abnormality. Through the integration of biomarker data representing inflammatory status and metabolic dysfunction, doctors are able to determine the unique pathophysiologic profile of women and adjust treatment strategies accordingly. Insulin-sensitizing treatments may be especially beneficial for women whose PCOS is primarily caused by insulin resistance. Anti-inflammatory treatments may help women with severe inflammatory signatures.Anti-inflammatory medications may be beneficial for women with severe inflammatory signs. Dyslipidemia in women may necessitate rigorous lipid control. With the potential to improve treatment results and better therapeutic intervention alignment with underlying pathophysiology, this biomarker-guided, customized approach is a significant improvement over one-size-fits-all approaches.[36]
11. PCOS Biomarkers: Genetic and Epigenetic
PCOS has a complicated aetiology that involves complex interactions between inherited genetic predisposition and epigenetic changes brought on by the environment. Recent developments in high-throughput omics technologies, genome-wide association studies (GWAS), and epigenomic profiling have identified several genes and molecular pathways that underlie the hormonal imbalances, metabolic disorders, and ovarian dysfunction associated with PCOS. Additionally, the crucial role of the gut microbiota is becoming increasingly recognized, making microbial profiling a promising area in PCOS diagnoses.[38]
11.1 Genetic Biomarkers
Potential Susceptibility Genes and Functional Roles
Through GWAS and rigorous candidate gene study, researchers have found several genetic variations linked to PCOS susceptibility. DENND1A controls vesicle trafficking and androgen biosynthesis, which increases the risk of overproducing androgens. Follicle-stimulating hormone and luteinizing hormone receptors are encoded by FSHR and LHCGR, which impact follicular growth patterns and the ovarian response to gonadotropin stimulation. Genetic variants significantly impact susceptibility and severity of insulin resistance, which affects 50–70% of women with PCOS. THADA, INS, INSR, and IRS1 are directly implicated in insulin signaling and metabolic homeostasis. SIRT1 is associated with oxidative stress response, cellular energy homeostasis, and metabolic balance. Other genes that impact important PCOS pathophysiologic pathways, such as steroidogenesis, folliculogenesis, and inflammatory responses, include TGF-β1 (inflammatory and steroidogenic regulator), FOXO1 (reproductive and metabolic transcription factor), and ESR1/ESR2 (estrogen receptors.[39]
Population Specificity and Polygenic Nature
Instead of a single gene defect, PCOS is the result of intricate interactions between several genetic variations. Significant genetic variation both within and between populations is produced by this polygenic inheritance mechanism. Well-known susceptibility single nucleotide polymorphisms (SNPs) like rs11171739 and rs17186366 have been reproduced by GWAS across a variety of ethnic groups, including North Indian communities, while also discovering population-specific genetic variants absent in other populations. The significance of conducting research in multiple populations is highlighted by this population-specific genetic architecture, which reflects both population-specific genetic backgrounds and shared underlying biological mechanisms.[40]
11.2 Epigenetic Biomarkers
DNA Methylation Changes
Epigenetic modifications—chemical changes that modify gene activity without altering the underlying DNA sequence—have a substantial effect on gene expression in PCOS. PCOS has been linked to aberrant patterns of DNA methylation at CpG islands, either hypomethylation (insufficient methylation for excessive expression) or hypermethylation (excessive methylation suppressing gene expression). (41) PCOS women exhibit dysregulated methylation patterns in genes related to steroidogenesis, insulin signaling, and inflammatory processes, including the estrogen production enzyme CYP19A1. PCOS symptoms are sustained by these abnormal methylation states, which cause dysregulated gene activity. Because of their dynamic methylation, these epigenetic changes may be altered by pharmacological or lifestyle changes.[41
11.3 Histone Modifications
Histone acetylation and methylation changes are linked to PCOS, especially at H3K9 and H3 acetylation patterns. DNA sections that are loosely structured (transcriptionally active) or firmly condensed (transcriptionally silent) are determined by these histone chemical changes that change chromatin structure. The chromatin structure and gene transcription of genes linked to metabolic processes and the formation of ovarian follicles are directly impacted by the histone alterations that are a hallmark of PCOS. Insulin resistance and the formation of ovarian follicles are two important PCOS pathophysiologic processes that are impacted by these long-lasting transcriptional alterations.[41]
11.4 Non-Coding RNAs and MicroRNAs
MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs), like SNHG5, control post-transcriptional gene expression. Target gene overexpression or suppression in PCOS is caused by dysregulated miRNA and lncRNA expression. In particular, these dysregulated non-coding RNAs disrupt normal granulosa cell activity and death, resulting in aberrant follicle development—poorly developed follicle accumulation instead of normal dominant follicle selection for ovulation.[38]
Functional Consequences
The abnormal gonadotropin responses that characterize PCOS are directly influenced by genetic variations in FSHR and LHCGR. Variants in INSR and IRS1 that are inherited or epigenetically altered have a significant impact on systemic and ovarian insulin resistance. Diet, exercise, stress, and exposures are examples of environmental and lifestyle factors that affect gene expression at the epigenetic level, explaining phenotypic heterogeneity in PCOS presentation and the way that identical genetic variants result in distinct clinical presentations in different people.[42] Together, these molecular biomarkers suggest possible directions for tailored treatment plans and targeted therapeutic interventions, allowing medical professionals to predict which complications specific women are more likely to experience and adjust preventative and therapeutic approaches accordingly.[41]
12. Metabolomic and Proteomic Biomarkers
Numerous proteins with altered expression in PCOS women have been found through extensive proteome studies looking at protein expression in blood and follicular fluid.[17]
The inflammatory regulator and protease inhibitor alpha-1 antitrypsin (A1AT) is elevated in newly diagnosed PCOS and correlates with androgen levels as well as inflammatory indicators like TNF-α and IL-6, indicating dual involvement in both chronic inflammation and androgen control. [43] While HIST1H4A (histone H4) is a risk factor for PCOS, TREML1 (triggering receptor expressed on myeloid cells-like 1) is a protective factor. With an area under the receiver operating characteristic curve (AUC) of 0.977, machine learning models utilizing these protein biomarkers significantly outperform traditional biomarker diagnosis accuracy.[44] Proteins associated in oxidative stress and immunological regulation, haptoglobin chains, and complement components are all expressed differently in PCOS samples. These modified protein biomarkers provide insight into basic PCOS pathophysiologic processes such as inflammation, metabolic dysfunction, and ovarian anomalies, potentially leading to the development of more accurate proteomic-based diagnostic panels.[45]
12.1 Metabolomic Biomarkers: Altered Metabolic Profiles
Using LC-MS and NMR spectroscopy, metabolomic profiling has identified several altered metabolic pathways in PCOS. Elevated long-chain fatty acids in fatty acid metabolism indicate improved lipolysis and changed lipid consumption .[46] Differences between aromatic and branched-chain amino acids in amino acid metabolism point to insulin resistance and more general metabolic disorders . [47] Significant changes in organic acid metabolism and oxidative stress markers, such as phenolamides, oxidative products, and benzoic acid modifications, indicate that increased oxidative stress directly damages cellular components and impairs ovarian follicle function. .[48]
12.2 Integration of Multiple Omics Approaches
Research that methodically integrates metabolomic and proteome data shows that alterations in several biological systems cooperate. Changes in glycolytic enzymes, inflammatory proteins, and lipid metabolism all contribute to the pathophysiology of PCOS. TGFBI and TXNIP proteins, for instance, are involved in the PCOS-related dysregulation of glycolysis. By identifying more reliable, repeatable biomarker signatures and deeper mechanistic insights, integrative omics methods lay the groundwork for creating really customized therapeutic interventions.[46]
13. Gut Microbiome as a Diagnostic Biomarker
Given its vital functions in hormone balance, inflammatory management, and metabolic control, the gut microbiota is becoming more widely acknowledged as a useful diagnostic marker in PCOS. Recent research has shown specific microbial signatures associated with PCOS that can be used as non-invasive biomarkers for phenotyping, diagnosis, and monitoring drug response, providing straightforward evaluation by stool analysis instead of invasive procedures.
13.1 Microbiome Composition Changes
Reduced microbial diversity and obvious compositional alterations, such as increased pathogenic bacteria (Bifidobacterium and Enterobacteriaceae) and decreased helpful bacteria (Bacteroides and Prevotella), are common in women with PCOS. The degree of hyperandrogenism, the existence of obesity, and the severity of insulin resistance are all strongly correlated with this dysbiosis pattern.[49]
13.2 Mechanistic Connections
Beneficial bacteria that ferment dietary fiber create short-chain fatty acids (SCFAs), which have a substantial impact on host metabolism by affecting lipid metabolism, improving insulin sensitivity, and regulating inflammatory pathways. The production of SCFA is reduced in dysbiotic microbiota with fewer beneficial bacteria, eliminating protective metabolic effects. When the barrier is disrupted by dysbiosis, intestinal permeability increases. Bacterial lipopolysaccharides (LPS) can enter the bloodstream when intestinal epithelial tight connections are disrupted. This can result in systemic endotoxemia and the persistent low-grade inflammation that characterizes PCOS. This establishes direct biological connections between PCOS inflammation and dysbiosis. Bidirectional communication between the microbiota and systemic hormones is described by the gut-hormone axis. Through the estrobolome—microbial genes encoding enzymes that metabolize estrogen—the microbiota controls the metabolism of sex hormones. Dysbiotic bacteria exhibit modified estrogen metabolism, impacting circulating estrogen levels and the equilibrium between metabolic and reproductive processes.[50]
13.3 Diagnostic Evidence and Clinical Applications
In PCOS, microbial profiling via stool analysis finds dysbiosis patterns with good sensitivity and specificity. Microbial metabolites or certain bacterial taxa are used as prognostic markers for PCOS severity and diagnosis. When gut microbiome data is combined with metabolic and hormonal profiles through machine learning, combining microbial, biochemical, and hormonal data into cohesive diagnostic algorithms, diagnostic accuracy increases significantly. Microbial fingerprint-based phenotypic classification offers insights into illness heterogeneity and customizes treatment strategies.[51]
13.4 Therapeutic Consequences
Early PCOS detection is made possible by microbiome-based diagnostics, especially in women with early-stage or asymptomatic PCOS. The use of therapeutic techniques to modify gut flora has significant potential as an adjuvant treatment for PCOS. Probiotics (beneficial live bacteria administration), prebiotics (dietary components selectively feeding beneficial bacteria), dietary modifications (macronutrient and fiber content changes), and fecal microbiota transplantation (FMT) (healthy donor microbiota transfer) are some of the intervention modalities that alter dysbiotic patterns. Microbiome biomarkers can be used to track the effectiveness of microbiota-modifying therapies, enabling the tracking of whether therapeutic approaches successfully restore eubiotic composition and correlate with changes in clinical PCOS manifestations.[51]
14. Advanced Techniques for Imaging and Radiomics
MRI radiomics: Using machine learning-based radiomic features from T2-weighted pelvic MRIs, PCOS patients and controls can be discriminated with good accuracy (AUC ~0.81, accuracy ~83%). The Light Gradient Boosting Machine (LightGBM) model performed exceptionally well, especially in obese patients who might not be a good candidate for transvaginal ultrasonography. [52] High-resolution ultrasound: Automated follicle counts and improved follicle imaging can improve morphological diagnosis. New follicular thresholds and ovarian size parameters are being developed in order to improve PCOS diagnosis.[53] Radiomic biomarkers use texture, shape, and signal intensity characteristics from imaging data to characterize ovarian tissue heterogeneity associated with PCOS.
15. AI and Machine Learning in the Diagnosis of PCOS
AI/ML algorithms analyze large and complex datasets, including clinical, biochemical, genetic, imaging, and multi-omics data, to detect and classify PCOS with accuracy often exceeding 90%. Examples of frequently used AI methods include Support Vector Machines (SVM), Random Forests, Gradient Boosting, and deep learning models created especially for PCOS detection. Artificial intelligence models can predict reproductive outcomes, insulin resistance, and hyperandrogenism, facilitating early diagnosis and customized therapy planning.[54] By improving the clarity and transparency of the PCOS diagnosis decision-making procedures Clinicians are beginning to recognize AI (XAI) solutions .[55] AI enhances primary care screening by raising detection rates and lowering misdiagnosis when it is integrated into imaging and electronic health records.. [56]
16. Clinical Utility and Validation
Validation of hormone markers: Studies highlight the importance of cross-population validation of biomarkers such anti-Müllerian hormone (AMH), free androgen index (FAI), and sex hormone-binding globulin (SHBG). Validation includes determining cutoff values, assessing sensitivity and specificity, and comparing with clinical features. For example, standardized AMH assays for diagnostic purposes are being verified using age-specific reference ranges. [57] Microbiome and metabolomic biomarkers: Several research demonstrate that serum metabolomic panels and gut microbiota profiles are reliable and practical in distinguishing PCOS; nevertheless, further validation studies are still necessary before therapeutic usage.[51] Imaging biomarkers: The repeatability and diagnostic effectiveness of ultrasound and radiomics are being verified. Machine learning-enhanced photo analysis has promise for standardizing morphological criteria and reducing operator variability. [46]
17. Future Perspectives and Research Directions
Integration of multi-omics with AI: Advances in genomics, proteomics, metabolomics, and microbiome profiling will be combined with AI to enable personalized and precise diagnosis. To validate multi-omics platforms, pilot studies are being carried out; the ultimate goal is large cohort validation.[46] Standardization of biomarkers: Consensus standards for test standardization, cutoff thresholds, and clinical procedures must be established in order to incorporate new biomarkers into standard practice. Interventional and longitudinal studies: By assessing biomarkers' ability to predict cardiovascular, metabolic, and reproductive outcomes using longitudinal cohorts, future research will investigate their predictive and prognostic usefulness.[36] Novel biomarker discovery: Given the potential of omics-driven biomarkers such as microbiome signatures, inflammatory cytokines, and microRNAs, multi-center validation trials are required. Development of technology: Nanotechnology and electrochemical sensors are being used in the development of rapid point-of-care testing instruments. In resource-constrained environments like clinics, these tools will make real-time diagnosis possible.
CONCLUSION:
The complicated endocrine-metabolic illness known as polycystic ovary syndrome has long presented challenges to traditional diagnostic paradigms due to its multiple origin and diverse presentation. The urgent need for more accurate, validated, and clinically useful biomarkers is highlighted by the shortcomings of present diagnostic criteria, such as phenotypic variability, assay inconsistency, and poor sensitivity to metabolic risk. This thorough analysis has compiled new data from the hormonal, metabolic, inflammatory, genetic, proteomic, metabolomic, and microbiome domains, exposing a promising field of cutting-edge diagnostic technologies that could revolutionize the diagnosis and treatment of PCOS.
Automated phenotypic classification, risk stratification, and tailored treatment decision-making are made possible by the integration of cutting-edge technologies, including artificial intelligence, machine learning, and radiomics. When combined into multi-dimensional panels that address the syndrome's reproductive and cardiometabolic aspects, emerging biomarkers such AMH, kisspeptin, inhibins, metabolomic signatures, and gut microbiota profiles show higher diagnostic accuracy. Moreover, proteomic findings such as FGFBP1, METRNL, and LTA4H show diagnostic accuracy above 90%, indicating impending advancements in clinical use. Rigorous validation through large-scale, multiethnic cohort studies, standardization of assay procedures, creation of population-specific reference ranges, and proof of affordability and accessibility are all necessary for the transition from discovery to clinical practice. Longitudinal studies to evaluate biomarker value in predicting long-term metabolic, cardiovascular, and reproductive outcomes as well as therapy response monitoring must be given top priority in future research. Expanding access in situations with limited resources will need the development of quick, point-of-care diagnostic platforms that use electrochemical sensors and nanotechnology.
In the end, the confluence of precision medical techniques, digital health advancements, and multi-omics integration signals a paradigm change from syndrome-based diagnosis to molecularly defined endotypes. These new biomarkers and diagnostic techniques promise to significantly improve clinical outcomes, decrease diagnostic delays, and lessen the long-term health burden faced by women with PCOS worldwide by facilitating earlier detection, precise phenotyping, and targeted interventions catered to individual pathophysiological profiles. To ensure that these scientific advancements significantly improve patient care and quality of life, the future requires cooperative, interdisciplinary efforts.
REFERENCE
Dr. Subashini R, Dr. Nivethana Krupanidhi, Janani B S, Grace S, Gayathri M, Jayashree T, Novel Biomarkers and Innovative Diagnostic Strategies in Polycystic Ovary Syndrome, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 11, 4137-4157. https://doi.org/10.5281/zenodo.17722137
10.5281/zenodo.17722137
