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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cell Dev. Biol.</journal-id>
<journal-title>Frontiers in Cell and Developmental Biology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cell Dev. Biol.</abbrev-journal-title>
<issn pub-type="epub">2296-634X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1645127</article-id>
<article-id pub-id-type="doi">10.3389/fcell.2025.1645127</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cell and Developmental Biology</subject>
<subj-group>
<subject>Mini Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Metabolic state and female fertility in ART cycles: a summary of current advances</article-title>
<alt-title alt-title-type="left-running-head">Berger et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fcell.2025.1645127">10.3389/fcell.2025.1645127</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Berger</surname>
<given-names>Natascha</given-names>
</name>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2082594/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Brugger</surname>
<given-names>Katharina</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fluhr</surname>
<given-names>Herbert</given-names>
</name>
<uri xlink:href="https://loop.frontiersin.org/people/2162423/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
</contrib-group>
<aff>
<institution>Department of Obstetrics &#x26; Gynecology, Medical University of Graz</institution>, <addr-line>Graz</addr-line>, <country>Austria</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/112666/overview">Ariane Zamoner</ext-link>, Federal University of Santa Catarina, Brazil</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2925628/overview">Can Benlioglu</ext-link>, Ko&#xe7; University, T&#xfc;rkiye</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3003934/overview">Ana D Martins</ext-link>, University of Aveiro, Portugal</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Natascha Berger, <email>natascha.berger@medunigraz.at</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>09</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>13</volume>
<elocation-id>1645127</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>06</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>08</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Berger, Brugger and Fluhr.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Berger, Brugger and Fluhr</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>This mini review explores the evolving landscape of metabolic disturbances and their impact on female reproductive outcomes, with a particular focus on emerging molecular biomarkers and novel metabolic phenotypes. Metabolic health plays a pivotal role in female reproductive function, with well-established endocrine-metabolic disorders, such as polycystic ovary syndrome, obesity, and diabetes mellitus, known to impair fertility. This review explores these conditions, including less commonly studied phenotypes like normal weight obesity, metabolically obese normal weight, and metabolically healthy obesity, which challenge traditional diagnostic frameworks by presenting metabolic risk independent of body mass index. These underrecognized profiles can adversely affect ovarian physiology, endometrial receptivity, and assisted reproductive technology outcomes. The review further highlights potential biomarkers, including bile acids and advanced glycation end-products, as promising diagnostic and therapeutic targets. By integrating insights from metabolic regulation, endocrinology, and reproductive biology, this article emphasizes the need for a more nuanced, individualized approach to fertility assessment and treatment. Understanding these interconnections is vital for advancing personalized medicine, particularly in addressing unexplained infertility and optimizing assisted reproductive technology success.</p>
</abstract>
<kwd-group>
<kwd>infertility</kwd>
<kwd>metabolism</kwd>
<kwd>reproduction</kwd>
<kwd>IVF</kwd>
<kwd>biomarker</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Molecular and Cellular Reproduction</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Infertility affects 8%&#x2013;12% of women of reproductive age (<xref ref-type="bibr" rid="B7">Chambers et al., 2021</xref>) and is a growing global concern, underscored by over 1 million assisted reproductive technologies (ART) cycles reported in 40 European countries in 2019 (<xref ref-type="bibr" rid="B70">Smeenk et al., 2023</xref>). Despite ongoing efforts, ART success rates remain low at around 30% (<xref ref-type="bibr" rid="B70">Smeenk et al., 2023</xref>), largely due to the complex and multifactorial nature of infertility etiologies. Recent evidence highlights that metabolic disorders, marked by insulin resistance, low-grade systemic inflammation, abdominal obesity, adipose tissue dysfunction and dyslipidemia, commonly observed in obese women and women with polycystic ovary syndrome (PCOS), are directly implicated in reduced fertility (<xref ref-type="bibr" rid="B5">Broughton and Moley, 2017</xref>; <xref ref-type="bibr" rid="B19">Helvaci and Yildiz, 2024</xref>; <xref ref-type="bibr" rid="B88">Zhuang et al., 2024</xref>). Obesity and overweight are intricately linked to diminished pregnancy rates, heightened demands for gonadotrophins, and elevated occurrences of miscarriage (<xref ref-type="bibr" rid="B12">Dornelles et al., 2022</xref>; <xref ref-type="bibr" rid="B23">Hu et al., 2022</xref>; <xref ref-type="bibr" rid="B60">Qi et al., 2022</xref>). Moreover, a high BMI correlates with adverse pregnancy outcomes, including gestational diabetes, hypertension, and preterm labor (<xref ref-type="bibr" rid="B40">Madan et al., 2010</xref>; <xref ref-type="bibr" rid="B69">&#x160;imj&#xe1;k et al., 2018</xref>; <xref ref-type="bibr" rid="B36">Liu et al., 2019</xref>). The underlying mechanisms are versatile and encompass hormonal alterations due to hypothalamic-pituitary-ovarian axis disruption, derailed metabolism (insulin resistance, hyperglycemia, dyslipidemia), chronic inflammation (elevated levels of proinflammatory cytokines, e.g., IL-6, IL-1&#x3b2;, TNF-&#x3b1;) and mitochondrial dysfunction (enhanced oxidative stress, apoptosis, mitochondrial DNA damage) that ultimately induce alterations in the ovarian follicle microenvironment, that have been extensively reviewed elsewhere (<xref ref-type="bibr" rid="B68">Silvestris et al., 2018</xref>; <xref ref-type="bibr" rid="B18">Gonnella et al., 2022</xref>; <xref ref-type="bibr" rid="B50">Muhammad et al., 2023</xref>). Alarmingly, the World Obesity Federation highlights a striking uptick in the prevalence of maternal obesity within developed nations, which is projected to reach 45%&#x2013;50% by 2030 (<xref ref-type="bibr" rid="B56">Phelps et al., 2024</xref>). With obesity and related metabolic disorders on the rise, assessing metabolic risk factors is essential to optimize infertility treatments and personalize strategies for improving pre-conception health. This article reviews current evidence on how metabolic health influences female fertility, highlighting emerging perspectives and under-studied phenotypes, normal weight obesity (NWO), metabolically obese normal weight (MONW), and metabolically healthy obesity (MHO), in relation to reproductive outcomes. Additionally, it explores the potential of emerging molecules such as bile acids (BAs) and advanced glycation end-products (AGEs) as biomarker candidates, and concludes with an overview of current research gaps and future directions.</p>
</sec>
<sec id="s2">
<title>Emerging metabolic phenotypes and female fertility</title>
<p>Based on the World Health Organization guidelines, a body mass index (BMI) equal to or exceeding 25 kg/m<sup>2</sup> stratifies overweight and a BMI above 30 kg/m<sup>2</sup> obesity, respectively (<xref ref-type="bibr" rid="B38">Lobstein et al., 2023</xref>). The use of BMI remains the foremost widely accepted measure for evaluating overweight and obesity. However, the diagnostic utility of BMI is significantly limited due to its inability to differentiate between fat and lean mass, which may lead to misclassifications since individuals sharing the same BMI may exhibit markedly distinct fat distributions. Women tend to face a higher likelihood of being underrecognized for overweight or obesity based on BMI criteria alone (<xref ref-type="bibr" rid="B55">Peterson et al., 2014</xref>). This lack of discrimination may hinder accurate assessments of adiposity associated health risks and necessitates the integration of additional measures, such as waist circumference or percentage of body fat (%BF). Emerging data indicates that central adiposity (higher waist-hip ratio) predicts lower fecundability and live birth after in-vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) independent of BMI (<xref ref-type="bibr" rid="B35">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B80">Ye et al., 2025</xref>). Notably, recent evidence suggests that the negative impact of central obesity is even more pronounced in women with lower BMI (<xref ref-type="bibr" rid="B80">Ye et al., 2025</xref>). Based on the data of the National Health and Nutrition Examination Survey, threshold values for %BF were established by evaluating its correlation with the risk of developing metabolic syndrome at various BMI cut-off points. For women, the %BF thresholds were defined at 24%, 31%, 37%, and 43%, which correspond to BMI values of 18.5, 25, 30, and 35 kg/m<sup>2</sup>, respectively (<xref ref-type="bibr" rid="B86">Zhu et al., 2003</xref>). In this context, studies have highlighted the importance of differentiating individuals with NWO from those who are MONW. NWO is characterized by a BMI in the normal range (18.5&#x2013;24.9 kg/m2) but elevated %BF (<xref ref-type="bibr" rid="B48">Mohammadian Khonsari et al., 2022</xref>). MONW individuals present a normal BMI but high %BF and obesity-related metabolic disturbances, such as excess visceral fat, insulin resistance, dyslipidemia, hypertension, and elevated risk of type 2 diabetes mellitus (T2D) and cardiovascular events (<xref ref-type="bibr" rid="B57">Pluta et al., 2022</xref>). In NWO individuals, metabolic abnormalities are often subtler and frequently undetected, however, this phenotype is associated with an elevated risk of metabolic syndrome and cardiometabolic disease compared with individuals of normal BMI and %BF (<xref ref-type="table" rid="T1">Table 1</xref>) (<xref ref-type="bibr" rid="B48">Mohammadian Khonsari et al., 2022</xref>). A cross-sectional study in Korea found that men and women with NWO were 2.7 and 1.9 times more likely to develop metabolic syndrome, respectively, compared to those with a normal BMI and %BF (<xref ref-type="bibr" rid="B28">Kim et al., 2023</xref>). A study comparing 326 males and 641 females revealed that 26% of males and 38% of females within the normal BMI range had a %BF above the respective cutoffs of 25% and 35% (<xref ref-type="bibr" rid="B32">Lahav et al., 2023</xref>). Furthermore, they showed that even a slightly elevated waist circumference (&#x3e;88 cm in women) can identify 60% of NWO individuals at risk for metabolic syndrome (<xref ref-type="bibr" rid="B32">Lahav et al., 2023</xref>). A recent study on NWO found that 15.8% of 469 normal-weight women had elevated %BF (&#x2265;31%), which was associated with reduced reproductive outcomes, including lower antral follicle counts, numbers of retrieved oocytes, fertilized oocytes, high-quality embryos on day 3 post fertilization and cleaved embryos (<xref ref-type="bibr" rid="B79">Yao et al., 2024</xref>). Interestingly, these findings stand in contrast to previous research, which failed to identify disparities in antral follicle counts or the quantity of retrieved oocytes between women categorized by %BF status. (<xref ref-type="bibr" rid="B27">Kim et al., 2021</xref>). Both studies found no differences in early pregnancy outcomes, including implantation, biochemical pregnancy, and clinical pregnancy rates, when women were stratified by %BF (<xref ref-type="bibr" rid="B27">Kim et al., 2021</xref>; <xref ref-type="bibr" rid="B79">Yao et al., 2024</xref>). In a large BMI-stratified IVF cohort, MONW had lower biochemical pregnancy rates than metabolically healthy normal-weight counterparts, with high blood pressure identified as a significant risk factor for this outcome (<xref ref-type="bibr" rid="B11">Ding et al., 2025</xref>). However, variations in cardiometabolic risk factors within the same BMI category appeared to have limited impact on live-birth rates (<xref ref-type="bibr" rid="B11">Ding et al., 2025</xref>).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Criteria for defining NWO, MONW and MHO phenotypes.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Phenotype</th>
<th align="left">Characterization</th>
<th align="left">Increased risk of<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">NWO (<xref ref-type="bibr" rid="B48">Mohammadian Khonsari et al., 2022</xref>)</td>
<td align="left">BMI 18.5&#x2013;24.9 kg/m2<break/>BF% &#x3e;32<break/>Central obesity</td>
<td align="left">hyperglycemia, insulin resistance, hypertension, dyslipidemia, metabolic syndrome</td>
</tr>
<tr>
<td align="left">MONW (<xref ref-type="bibr" rid="B64">Ruderman et al., 1998</xref>; <xref ref-type="bibr" rid="B57">Pluta et al., 2022</xref>)</td>
<td align="left">BMI 18.5&#x2013;24.9 kg/m2<break/>BF% &#x2265;32<break/>Excess visceral fat, hyperinsulinemia and<break/>insulin resistance, dyslipidemia, PCOS</td>
<td align="left">metabolic syndrome, T2D<break/>cardiovascular events</td>
</tr>
<tr>
<td align="left">MHO (<xref ref-type="bibr" rid="B71">Smith et al., 2019</xref>)</td>
<td align="left">BMI &#x2265;25 kg/m2, &#x3c;35 kg/m2<break/>Absence of metabolic abnormalities or diagnosis &#x2264;2 of 5 metabolic syndrome components</td>
<td align="left">Cardiometabolic disturbances</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn1">
<label>
<sup>a</sup>
</label>
<p>compared to metabolically healthy normal weight individuals.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Importantly, the prevalence of NWO and MONW in women varies with age, showing that advancing age and concomitant menopause leads to an increased risk of metabolic abnormalities (<xref ref-type="bibr" rid="B85">Zheng et al., 2020</xref>; <xref ref-type="bibr" rid="B32">Lahav et al., 2023</xref>). One explanation is that estrogen may act as a protective factor in maintaining metabolic health in normal-weight females, since the loss of estrogen signaling in menopausal women leads to a preferential increase in visceral fat (<xref ref-type="bibr" rid="B20">Hetem&#xe4;ki et al., 2021</xref>).</p>
<p>Of further specific interest are obese individuals demonstrating minimal or no metabolic disturbances, a condition termed MHO (<xref ref-type="table" rid="T1">Table 1</xref>) (<xref ref-type="bibr" rid="B71">Smith et al., 2019</xref>). Large-scale genomic studies have identified genetic variants associated with favorable cardiometabolic profiles despite increased adiposity, often located in or near genes involved in adipogenesis, fat distribution and insulin signaling, suggesting a genetic basis for this phenotype (<xref ref-type="bibr" rid="B24">Huang et al., 2018</xref>). A recent study of women aged 20&#x2013;45 found that both metabolically healthy and unhealthy individuals with obesity had similar infertility risk, suggesting obesity itself is a key factor regardless of metabolic status. However, metabolically unhealthy obese individuals exhibited a significantly pronounced risk of infertility compared to MHO individuals (<xref ref-type="bibr" rid="B73">Tang et al., 2023</xref>). Similarly, the S-PRESTO preconception cohort found reduced fecundability associated with metabolic disease, predominantly in overweight and obese women, whereas no reduction was observed in those with metabolically healthy profiles by either metabolic syndrome criteria or HOMA-IR (<xref ref-type="bibr" rid="B39">Loy et al., 2022</xref>). Complementary plasma proteome analysis revealed that reproductive system development pathways were significantly downregulated in MHO individuals compared to lean healthy controls (<xref ref-type="bibr" rid="B47">Mir et al., 2025</xref>). In summary the current body of literature indicates that obesity, irrespective of metabolic health, is associated with impaired fertility, suggesting that weight management should be a priority in reproductive health strategies, even among metabolically healthy individuals. While there is extensive research on the impact of obesity on fertility, the specific effects of NWO, MONW and MHO on fertility, <italic>in vitro</italic> embryo development and pregnancy outcomes remain areas that require further investigation.</p>
</sec>
<sec id="s3">
<title>Metabolic disorders and metabolite profiles in female infertility</title>
<p>PCOS is a common endocrine disorder affecting 4%&#x2013;21% of women of reproductive age and is a leading cause of anovulatory infertility (<xref ref-type="bibr" rid="B37">Lizneva et al., 2016</xref>). Obesity, present in 50%&#x2013;80% of PCOS cases, plays a central role in the pathophysiology of PCOS by promoting insulin resistance, which affects approximately 44%&#x2013;70% of affected women (<xref ref-type="bibr" rid="B65">Sam, 2007</xref>; <xref ref-type="bibr" rid="B9">Diamanti-Kandarakis and Dunaif, 2012</xref>). However, the interplay between obesity and PCOS is complex and appears to be bidirectional: it remains unclear whether PCOS predisposes women to weight gain or if obesity itself initiates the metabolic disturbances that culminate in PCOS. In fact, both obese and non-obese women with PCOS exhibit more adverse metabolic profiles and increased visceral adiposity compared to age- and BMI-matched controls. Non-obese individuals often display features of the MONW phenotype, including hyperinsulinemia, insulin resistance, and elevated intra-abdominal fat mass (<xref ref-type="bibr" rid="B64">Ruderman et al., 1998</xref>; <xref ref-type="bibr" rid="B66">Satyaraddi et al., 2019</xref>). Moreover, insulin resistance is present in approximately 80% of obese PCOS patients and even in 20% of their nonobese counterparts, underscoring that significant metabolic risk persists regardless of BMI (<xref ref-type="bibr" rid="B66">Satyaraddi et al., 2019</xref>). Similarly, women with diabetes encounter reproductive health issues including a higher prevalence of oligomenorrhea, irregular menses, subfertility, adverse pregnancy outcomes, and early menopause (<xref ref-type="bibr" rid="B74">Thong et al., 2020</xref>; <xref ref-type="bibr" rid="B61">Qin et al., 2023</xref>). Since these reproductive issues are partially attributed to concomitant obesity and PCOS, studies exclusively discerning the impact of diabetes are of great importance. Women with T2D may experience equal or greater fertility risks than those with type 1 diabetes mellitus (T1D), despite a shorter disease duration (<xref ref-type="bibr" rid="B74">Thong et al., 2020</xref>; <xref ref-type="bibr" rid="B42">Mattsson et al., 2021</xref>). Aberrant insulin actions and hyperglycemia are significant drivers that contribute to ovarian dysfunction (<xref ref-type="bibr" rid="B13">Dupont and Scaramuzzi, 2016</xref>). The ovary expresses insulin receptors in granulosa cells, theca cells, and stromal tissue. Insulin signaling, through insulin receptors and insulin-like growth factor-1 receptors, can mimic follicle-stimulating hormone (FSH) and luteinizing hormone (LH) actions, a phenomenon known as the co-gonadotropin effect, enhancing androgen, estrogen, and progesterone production (<xref ref-type="bibr" rid="B13">Dupont and Scaramuzzi, 2016</xref>). By mimicking gonadotropins, insulin drives early follicular growth and contributes to polycystic ovarian morphology (<xref ref-type="bibr" rid="B31">Kwintkiewicz and Giudice, 2009</xref>). Furthermore, in human granulosa cells, insulin promotes free fatty acid synthesis and synergizes with luteinizing hormone to upregulate key sterol-regulatory genes (<xref ref-type="bibr" rid="B67">Sekar et al., 2000</xref>; <xref ref-type="bibr" rid="B62">Richardson et al., 2005</xref>). In obese PCOS patients with insulin resistance, follicular fluid contains significantly elevated levels of mono- and polyunsaturated fatty acids, which are linked to reduced oocyte quality and increased embryo fragmentation (<xref ref-type="bibr" rid="B52">Niu et al., 2014</xref>). Supporting these findings, PCOS granulosa cells exhibit dysregulated expression of genes involved in lipid metabolism, fatty acid biosynthesis, and steroidogenesis, including upregulation of lipoxygenases that promote pro-inflammatory lipid mediator production (<xref ref-type="bibr" rid="B34">Li et al., 2017</xref>; <xref ref-type="bibr" rid="B90">Liao et al., 2022</xref>).</p>
<p>As key metabolic regulators of glucose and lipid homeostasis and modulators of systemic inflammatory balance bile acids (BAs) have emerged as crucial biomolecules in PCOS pathophysiology (<xref ref-type="bibr" rid="B15">Fleishman and Kumar, 2024</xref>). Since abnormal circulating BA profiles are associated with metabolic disorders, including obesity and T2D (<xref ref-type="bibr" rid="B33">Li and Chiang, 2014</xref>; <xref ref-type="bibr" rid="B59">Qi et al., 2021</xref>), and complications and diseases during pregnancy (<xref ref-type="bibr" rid="B6">Brouwers et al., 2015</xref>), there is a growing interest in the underlying molecular mechanisms and the establishment of BAs as biological markers to determine pathological changes. In PCOS patients, an elevation of distinct BA classes and direct associations of BA species with insulin and androgen levels were demonstrated (<xref ref-type="bibr" rid="B83">Zhang et al., 2019</xref>; <xref ref-type="bibr" rid="B81">Yu et al., 2023</xref>). Moreover, shot-gun sequencing of stool samples in PCOS identified a gut microbiota imbalance linked to reduced glycine- and taurine-conjugated BA species (<xref ref-type="bibr" rid="B58">Qi et al., 2019</xref>). Fecal microbiota transplantation from PCOS patients induced ovarian dysfunction, insulin resistance, disrupted BA metabolism and infertility, alongside reduced interleukin-22 secretion in mice. BA treatment stimulated IL-22 production and ameliorated PCOS features, highlighting gut microbiota, BA metabolism and IL-22 modulation as potential therapeutic targets (<xref ref-type="bibr" rid="B58">Qi et al., 2019</xref>).</p>
<p>Chronic hyperglycemia further promotes the formation of advanced glycation end-products (AGEs). AGEs are heterogeneous and nondegradable molecules formed endogenously or ingested through diet, via non-enzymatic reactions between reducing sugars and free amino groups of proteins, lipids, or nucleic acids, disrupting the normal function of these molecules. Accumulation of AGEs induces tissue damage through receptor-independent binding to the extracellular matrix or receptor-dependent activation of receptor for advanced glycation end-products (RAGE), both of which trigger inflammatory and oxidative stress responses (<xref ref-type="bibr" rid="B43">Mengstie et al., 2022</xref>). Additionally, the soluble receptor for AGEs (sRAGE) circulates systemically and acts as a decoy, mitigating AGE-induced damage by preventing their interaction with RAGE (<xref ref-type="bibr" rid="B44">Merhi, 2014</xref>). In follicular fluid, sRAGE protein levels were directly associated with the number of oocytes, follicles, ovarian sensitivity index, embryonic development, and successful clinical pregnancy outcomes in women undergoing ART, proposing sRAGE levels as a predictor for ART outcomes (<xref ref-type="bibr" rid="B45">Merhi et al., 2014</xref>; <xref ref-type="bibr" rid="B51">Nejabati et al., 2017</xref>; <xref ref-type="bibr" rid="B89">Li et al., 2017</xref>). Accordingly, the presence of AGEs in serum and follicular fluid of women undergoing ART has been significantly correlated with poor follicular and embryonic development, as well as a reduced likelihood of achieving an ongoing pregnancy (<xref ref-type="bibr" rid="B26">Jinno et al., 2011</xref>). Further, overweight and obese women have significantly lower serum sRAGE concentrations when compared with normal-weight women undergoing ART (<xref ref-type="bibr" rid="B45">Merhi et al., 2014</xref>). This finding is in line with previous studies demonstrating low plasma sRAGE levels in obese women and diabetic patients, which are associated with high BMI, blood pressure-, triglyceride-, HbA1c-levels, an increased insulin resistance index and enhanced thromboxane biosynthesis, potentially contributing to obesity-related metabolic and vascular disease (<xref ref-type="bibr" rid="B30">Koyama et al., 2005</xref>; <xref ref-type="bibr" rid="B75">Vazzana et al., 2012</xref>). An <italic>in vitro</italic> study examining the impact of AGEs on insulin signaling and glucose transport using a human ovarian granulosa cell line demonstrated that glycated albumin inhibits PI3K-specific AKT phosphorylation and prevents Glut-4 translocation to the cell membrane, indicating that intra-follicular accumulation of AGEs may interfere with physiological functions of granulosa cells contributing to impaired follicular development (<xref ref-type="bibr" rid="B10">Diamanti-Kandarakis et al., 2016</xref>). Immunohistochemical analysis has shown elevated levels of AGEs and RAGE in granulosa and theca cells of women with PCOS and demonstrated a direct association between hyperandrogenism and AGEs in the condition (<xref ref-type="bibr" rid="B16">Garg and Merhi, 2016</xref>; <xref ref-type="bibr" rid="B2">Azhary et al., 2020</xref>). Of note, administration of the hydrophilic tertiary BA tauroursodeoxycholic acid, a clinically used endoplasmic reticulum stress inhibitor, significantly reduced RAGE and AGE expression in granulosa cells and decreased the number of atretic follicles in PCOS mice (<xref ref-type="bibr" rid="B2">Azhary et al., 2020</xref>; <xref ref-type="bibr" rid="B82">Yuan et al., 2024</xref>).</p>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The presence of hormonal and metabolic derailments as seen in PCOS, diabetes, NWO, MONW, and MHO underscores the multifaceted nature of infertility etiologies. Unexplained infertility in approximately 15% of couples further emphasizes the need to investigate less apparent disease patterns and delve into molecular pathways influencing female fertility (<xref ref-type="bibr" rid="B63">Romualdi et al., 2023</xref>). Further investigation of NWO, MONW, and MHO phenotypes in reproductive biology is essential, as limited research exists and these conditions are often overlooked, underscoring the need to incorporate comprehensive metabolic assessments into routine clinical care. Women exhibiting a normal BMI are frequently underdiagnosed as studies have shown that approximately 40% of 641 screened women had a BF% above the recommended cutoffs (<xref ref-type="bibr" rid="B32">Lahav et al., 2023</xref>). Prospective epidemiological studies are essential to validate these findings and examine the long-term impact of NWO, MONW, and MHO on female fertility.</p>
<p>PCOS diagnosis involves multiple markers, including androgen levels and insulin resistance indicators, to characterize the syndrome&#x2019;s phenotype. Women with PCOS also display adverse lipid profiles and elevated cardiovascular risk, emphasizing the need for targeted metabolic interventions. In this context, BAs have emerged as potential diagnostic biomarkers and novel systemic signaling molecules (<xref ref-type="bibr" rid="B76">V&#xed;tek and Haluz&#xed;k, 2016</xref>; <xref ref-type="bibr" rid="B14">Fiorucci et al., 2021</xref>). Particularly pharmacological strategies to modulate the activity of the nuclear BA receptor Farnesoid X Receptor and the G-protein coupled BA receptor TGR5 holds promise for treating fatty liver diseases, obesity, diabetes, and related disorders (<xref ref-type="bibr" rid="B33">Li and Chiang, 2014</xref>). Importantly, the composition of BAs as well as the level of total BAs in follicular fluid have been reported to affect follicular maturation and steroidogenesis in different animal models (<xref ref-type="bibr" rid="B72">Takae et al., 2019</xref>; <xref ref-type="bibr" rid="B77">Wei et al., 2022</xref>; <xref ref-type="bibr" rid="B87">Zhu et al., 2025</xref>). Although promising preclinical evidence supports a significant impact of BAs on the intrafollicular milieu in PCOS, more detailed basic research utilizing human <italic>in-vitro</italic> models are necessary to establish the efficacy of specific BA-targeting interventions.</p>
<p>Moreover, chronic hyperglycemia, oxidative stress, and chronic low-grade inflammation are key factors known to drive the endogenous formation of AGEs. These compounds have been implicated in the pathogenesis and progression of numerous chronic diseases, including T2D, cardiovascular disease, Alzheimer&#x2019;s disease, and inflammatory bowel diseases (<xref ref-type="bibr" rid="B54">Perrone et al., 2020</xref>; <xref ref-type="bibr" rid="B43">Mengstie et al., 2022</xref>). The potential of anti-AGE strategies, including agents such as metformin, to alleviate AGE-related dysfunctions in PCOS has been demonstrated (<xref ref-type="bibr" rid="B46">Merhi et al., 2019</xref>). Furthermore, treatment with tauroursodeoxycholic acid, has shown promise in reducing AGE and RAGE expression and improving ovarian health in PCOS models (<xref ref-type="bibr" rid="B2">Azhary et al., 2020</xref>). The mechanisms through which anti-AGE interventions may exert their effects include reducing oxidative stress, improving insulin sensitivity, and modulating inflammatory pathways, which are critical in the management of PCOS. Understanding the AGE-RAGE/sRAGE axis in ovarian dysfunction, especially in women with PCOS, may enhance our understanding of pathologic female reproductive mechanisms. Despite the critical role of AGEs in various disease mechanisms, there is currently no standardized detection method for these compounds, nor is there routine monitoring in clinical practice. Advancing our understanding of AGEs&#x27; formation and their pathological impacts could pave the way for improved diagnostic and therapeutic strategies.</p>
</sec>
<sec id="s5">
<title>Research gaps</title>
<sec id="s5-1">
<title>Beyond BMI&#x2014;better phenotyping</title>
<p>Given BMI&#x2019;s limitations as a proxy for adiposity and metabolic disease risk, adjunct anthropometrics (e.g., waist-to-hip ratio) and body-composition measures (e.g., %BF) may offer clinically useful refinement. Further, rigid BMI-based criteria for offering or denying IVF may restrict equitable access without evidence of clinical benefit. Thresholds (often &#x2265;35&#x2013;40 kg/m<sup>2</sup>) vary widely across programs and are largely grounded in observational associations between higher BMI, lower ART success, and greater obstetric risk rather than randomized evidence (<xref ref-type="bibr" rid="B53">Penzias et al., 2021</xref>).</p>
</sec>
<sec id="s5-2">
<title>Insulin resistance&#x2014;Standardize and stratify</title>
<p>Insulin resistance, prevalent in PCOS and obesity-related infertility, is inconsistently defined in the literature, with most studies using surrogate indices (e.g., HOMA-IR, QUICKI, Belfiore&#x2019;s index) that vary in accuracy and underperform the euglycemic&#x2013;hyperinsulinemic clamp, particularly in lean women (<xref ref-type="bibr" rid="B17">Gayoso-Diz et al., 2013</xref>; <xref ref-type="bibr" rid="B3">Biernacka-Bartnik et al., 2023</xref>). This heterogeneity limits comparability, obscures prevalence in ART populations, and hampers reproducibility of outcome associations. Standardized, cardiometabolic-risk&#x2013;based and age-adjusted definitions, potentially integrating biomarkers such as insulin growth factor binding protein, adiponectin and ferritin combined with surrogate indices (<xref ref-type="bibr" rid="B41">Mart&#xed;nez-Garc&#xed;a et al., 2009</xref>; <xref ref-type="bibr" rid="B4">Brismar et al., 2023</xref>), could improve diagnostic precision and guide metabolic optimization in ART.</p>
</sec>
<sec id="s5-3">
<title>Lifestyle, weight-loss and pharmacotherapy interventions before ART</title>
<p>Major societies (European Society of Human Reproduction and Embryology (ESHRE) and the American Society for Reproductive Medicine (ASRM)) recommend lifestyle interventions for individuals with overweight/obesity to reduce weight, central adiposity, and insulin resistance. However, randomized controlled trails and meta-analyses indicate that pre-IVF weight-loss programs (diet/exercise &#xb1; medication) improve interim outcomes (e.g., unassisted conception) but have inconsistent or no effect on live birth for women proceeding to IVF (<xref ref-type="bibr" rid="B53">Penzias et al., 2021</xref>; <xref ref-type="bibr" rid="B25">Jeong et al., 2024</xref>). Pre-ART metabolic pharmacotherapies (metformin, anti-obesity pharmacotherapy including GLP-1 receptor agonists) are supported by small, heterogeneous studies that suggest potential benefit by emphasizing surrogate endpoints (oocyte yield, biochemical pregnancy) but require confirmation in large randomized controlled trails powered for live birth and safety (<xref ref-type="bibr" rid="B29">Kotlyar and Seifer, 2023</xref>).</p>
</sec>
</sec>
<sec id="s6">
<title>Future directions</title>
<p>Next-generation personalization in reproductive medicine will likely come from integrating multi-omics with clinical workflows, potentially improving non-invasive prediction of oocyte competence and embryo viability. Metabolomics of follicular fluid, serum, and embryo culture media can yield dynamic snapshots of energy metabolism, oxidative balance and profile metabolites acting as crucial bioactive signaling molecules (<xref ref-type="bibr" rid="B22">Hood et al., 2022</xref>; <xref ref-type="bibr" rid="B1">Alizadeh Moghadam Masouleh et al., 2025</xref>; <xref ref-type="bibr" rid="B84">Zhang et al., 2025</xref>). Standardized sampling/analytics and prospective validation, ideally supported by machine-learning, are essential to develop reliable tools that link metabolic profiles with clinical outcomes.</p>
<p>Further, the gut microbiota is a central regulator of female reproductive health. The bidirectional &#x201c;gut&#x2013;reproductive axis,&#x201d; mediated by interconnected immune, metabolic, and neuroendocrine networks, facilitates communication between the intestinal microbiota and reproductive organs (<xref ref-type="bibr" rid="B49">Moustakli et al., 2025</xref>). Dysbiosis, marked by altered short-chain fatty acid profiles, disrupted BA metabolism, and impaired gut barrier integrity, can perturb host energy balance, promote chronic inflammation, and contribute to metabolic disorders such as PCOS and obesity (<xref ref-type="bibr" rid="B58">Qi et al., 2019</xref>; <xref ref-type="bibr" rid="B78">Yao et al., 2023</xref>; <xref ref-type="bibr" rid="B49">Moustakli et al., 2025</xref>). Strategies to restore a healthy gut microbial profile, via dietary modification, prebiotics, probiotics, or targeted microbial therapeutics, hold promise for improving metabolic homeostasis and reproductive outcomes, though robust interventional evidence remains limited. Future research should focus on robust studies establishing causal relationships between the intestinal microbiome and reproductive disorders.</p>
<p>Lastly, pharmacogenetics represents an emerging avenue for personalization in ART, with significant potential to optimize drug selection and dosing in ovarian stimulation and ovulation induction. Variants in FSH and LH receptor genes have been shown to influence ovarian response to standard stimulation protocols, and early evidence indicates that genotype-guided gonadotropin selection may enhance cumulative pregnancy and live birth rates (<xref ref-type="bibr" rid="B8">Conforti et al., 2025</xref>; <xref ref-type="bibr" rid="B21">Hjelm&#xe9;r et al., 2025</xref>). These findings warrant confirmation in randomized controlled trials and may ultimately enable tailoring of stimulation regimens to each patient&#x2019;s metabolic&#x2013;hormonal profile (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Graphical summary of key points discussed. HPO- axis, Hypothalamic-pituitary-ovarian- axis; IL-6, Interleukin-6; IL-1&#x3b2;, Interleukin- 1beta; TNF-&#x3b1;, Tumor necrosis factor alpha; ROS, Reactive oxygen species; mtDNA, Mitochondrial DNA; NWO, Normal weight obesity; MONW, Metabolically obese normal weight; MHO, Metabolically healthy obesity; BAs, Bile acids; AGEs, Advanced glycation end-products; ART, Assisted reproductive technologies; Created in BioRender.</p>
</caption>
<graphic xlink:href="fcell-13-1645127-g001.tif">
<alt-text content-type="machine-generated">Diagram highlighting the effects of obesity on female fertility. The sections detail metabolic phenotypes and respective metabolic profiles and their direct impacts on fertility, including oocyte and embryo quality, implantation, and ART success. It outlines research gaps and future directions such as improved phenotyping and precision reproductive medicine.</alt-text>
</graphic>
</fig>
</sec>
</body>
<back>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>NB: Writing &#x2013; original draft, Writing &#x2013; review and editing. KB: Writing &#x2013; original draft, Writing &#x2013; review and editing. HF: Writing &#x2013; original draft, Writing &#x2013; review and editing.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. The study is funded through external research funding from the Clinical Department of Obstetrics at the University Hospital Graz, Medical University of Graz.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12">
<title>Abbreviations</title>
<p>AGE, Advanced glycation end-product; ART, Assisted reproductive technologies; BA, Bile acid; %BF, Body fat percentage; BMI, Body mass index; MHO, Metabolically healthy obesity; MONW, Metabolically obese normal weight; NWO, Normal weight obesity; PCOS, Polycystic ovarian syndrome; T1D, Type 1 diabetes mellitus; T2D, Type 2 diabetes mellitus; IVF/ICSI, In-vitro fertilization/intracytoplasmic sperm injection; RAGE, Receptor for advanced glycation end-products; FSH, Follicle-stimulating hormone; LH, Luteinizing hormone.</p>
</sec>
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