Lipidomic Remodeling by HILPDA in Granulosa Cells Impairs Ovarian Reserve Through Disruption of Mitochondrial and Endoplasmic Reticulum Homeostasis

Diminished ovarian reserve (DOR) is characterized by a decline in oocyte quantity and/or quality and represents a growing cause of female infertility, particularly among young women, yet its pathogenesis remains incompletely understood. Disordered lipid metabolism impairs folliculogenesis and steroidogenesis, thereby contributing to the pathological changes of DOR. Here, we identify hypoxia‐inducible lipid droplet‐associated protein (HILPDA), a regulator of lipid droplet biogenesis, as a potential contributor to DOR. We found that HILPDA was significantly upregulated in granulosa cells (GCs) from DOR patients and that its expression levels correlated with reduced ovarian reserve indicators and adverse assisted reproductive technology (ART) outcomes. Ovarian overexpression of HILPDA in mice promoted follicular atresia and disrupted the estrous cycle. In KGN cells, HILPDA overexpression suppressed proliferation and induced apoptosis. Mechanistically, HILPDA overexpression promoted excessive accumulation of triglyceride‐rich lipid droplets, accompanied by depletion of phospholipids, cholesteryl esters, and mitochondrial cardiolipin species. This lipid remodeling was associated with impaired estradiol biosynthesis, mitochondrial dysfunction, and endoplasmic reticulum stress activation. Genetic restoration of lipolysis via adipose triglyceride lipase (ATGL) overexpression or pharmacological inhibition of excessive lipid droplet formation alleviated HILPDA‐associated lipotoxicity and cellular dysfunction. Collectively, these findings suggest that HILPDA may play an important role in GC dysfunction in DOR through reprogramming lipid metabolism and indicate that targeting this pathway may represent a potential therapeutic strategy for DOR.

diminished ovarian reserve, endoplasmic reticulum stress, granulosa cells, HILPDA, lipid dysregulation, mitochondrial dysfunction HILPDA tilts the lipid balance toward storage: excessive triglyceride accumulation at the expense of structural and functional lipids triggers mitochondrial dysfunction, endoplasmic reticulum stress, and steroidogenic failure, ultimately leading to diminished ovarian reserve. 1. Introduction Diminished ovarian reserve (DOR), characterized by reduced oocyte quantity and/or quality, is associated with impaired ovarian function [1]. With a reported prevalence of 10%–35%, DOR is clinically characterized by premature primordial follicle depletion, accelerated follicular atresia, and impaired follicular development [2]. Notably, the prevalence of DOR is rising among young women, whose early‐onset form arises from multiple poorly defined etiological factors, including immune dysregulation, genetic predisposition, environmental insults, and chemotherapy or radiotherapy exposure [3]. Such adverse triggers lead to hallmark pathophysiological disturbances in the ovary: endoplasmic reticulum (ER) stress [4], oxidative stress [5, 6], inflammation [7, 8], and dysregulated energy metabolism [9, 10]. DOR is typically identified by reduced anti‐Müllerian hormone (AMH), decreased antral follicle count (AFC), and elevated basal follicle‐stimulating hormone (FSH). These ovarian reserve markers also constitute key components of the Bologna consensus for poor ovarian response [11] and the POSEIDON low‐prognosis stratification [12]. DOR may progress to premature ovarian insufficiency in some patients within several years [13]. GCs are vital for ovarian function, supporting folliculogenesis, steroidogenesis, and metabolic regulation [14]. In mammalian ovaries, bidirectional communication between oocytes and surrounding GCs occurs via transzonal projections and receptor‐ligand‐mediated paracrine signaling [15], suggesting that oocyte dysfunction in DOR may originate from aberrant GC regulation. Lipid metabolism is essential for maintaining GC function. In addition to supplying energy for follicular development through fatty acid β‐oxidation, it produces metabolites such as cholesterol, lipoproteins, and 14‐demethyl‐14‐dehydrolanosterol, which serve as precursors for steroid hormone synthesis and regulators of meiosis resumption [16]. Notably, enhanced lipid metabolism in mouse GCs has been shown to rejuvenate oocytes and extend reproductive lifespan [17]. Zhu et al. reported that reduced GC glucose uptake and mitochondrial dysfunction contribute to energy imbalance, inhibit AMPK signaling, restrict energy supply, and impair follicular development in DOR [18]. In addition, altered fatty acids and cholesterol in GCs may induce apoptosis via impaired mitochondrial ATP production, DNA repair, and steroidogenesis, collectively contributing to DOR [9, 19]. HILPDA expression is induced by diverse metabolic and stress stimuli (hypoxia, inflammation, β‐adrenergic activation) and is associated with intracellular lipid droplet formation and triglyceride (TG) storage regulation [20, 21]. Localized around the endoplasmic reticulum and lipid droplets, HILPDA is a selective endogenous inhibitor of ATGL in adipocytes and specific tumor cell types [22, 23]. ATGL catalyzes the initial and rate‐limiting step of TG hydrolysis [24]. Through its inhibition of ATGL, HILPDA regulates physiological lipid storage, glucose metabolism, and thermogenesis, and its lipid droplet‐promoting property further confers a survival advantage on hepatocellular carcinoma cells under hypoxia and nutrient deficiency‐related metabolic stress [25, 26, 27]. Beyond oncology, HILPDA also contributes to renal pathophysiology by disrupting fatty acid metabolism in renal tubular epithelial cells, leading to G2/M phase arrest and the upregulation of profibrotic factors, thereby driving tubulointerstitial fibrosis [28]. Notably, in the context of ovarian function and DOR, how this pivotal regulatory axis operates remains an open and compelling question. Here, we investigated whether HILPDA contributes to GC dysfunction and ovarian impairment by reprogramming lipid metabolism. 2. Materials and Methods 2.1. Study Population A total of 137 young women (≤ 35 years) undergoing ART at the Reproductive Medicine Center, the First Hospital of Lanzhou University were enrolled. Participants were divided into two groups: normal ovarian reserve (NOR) group (n = 70): (i) AMH > 2 ng/mL, (ii) AFC > 7. DOR group (n = 67): (i) AMH ≤ 1.1 ng/mL, (ii) AFC ≤ 7. The causes of infertility in the NOR group included tubal‐factor infertility, male‐factor infertility, and cervical or endometrial factors. The exclusion criteria for the DOR group included polycystic ovary syndrome, a history of ovarian surgery, ovarian cysts, endometriosis, thyroid dysfunction, and diabetes mellitus. 2.2. Collection of Granulosa Cells Patients received a gonadotropin‐releasing hormone antagonist protocol. After ovarian stimulation, follicular fluid was collected by transvaginal ultrasound‐guided puncture of follicles larger than 14 mm in diameter. Cumulus‐oocyte complexes were isolated for conventional in vitro fertilization or intracytoplasmic sperm injection, and the remaining follicular fluid from each patient was pooled for GC isolation. The pooled fluid was layered onto 50% Percoll solution (P8370, Solarbio) and centrifuged. The intermediate cell layer was collected using a Pasteur pipette, treated with red blood cell lysis buffer (R1010, Solarbio), washed with phosphate‐buffered saline, and the isolated GCs were assessed by microscopic examination. These cells were residual samples remaining after clinical use. 2.3. Animal Treatment Female C57BL/6 mice (8 weeks old) were purchased from HuachuangXinnuo (Jiangsu, China) and acclimatized for 2 weeks prior to experimental manipulation. At 10 weeks of age, bilateral intra‐ovarian injection of adeno‐associated virus 9 (AAV9) was performed in mice with the following treatment regimens: Vector group: injected with pAAV‐CAG‐EGFP (5 μL per ovary, titer ≥ 1 × 1013 vg/mL); HILPDA group: injected with pAAV‐CAG‐HILPDA‐P2A‐EGFP (5 μL per ovary, titer ≥ 1 × 1013 vg/mL). A blank control group without any treatment was included to verify successful AAV infection in both the Vector and HILPDA groups. Mice were anesthetized with 1% pentobarbital sodium. Following lower back shaving and disinfection with 75% alcohol, a 0.5‐cm bilateral oblique incision was made. The ovaries were exposed via blunt dissection, and a 5 μL syringe was used to slowly inject the virus into each ovary over approximately 3 min, until the ovarian capsule showed visible swelling. Hemostasis was achieved by compressing the injection site with sterile gauze. The ovary was then repositioned, and the incision was sutured. After a 33‐day observation period post‐AAV treatment, all mice were euthanized for tissue collection (via cervical dislocation following profound anesthesia induced by an intraperitoneal injection of 1% pentobarbital sodium at 50 mg/kg). All procedures adhered to aseptic techniques and approved institutional animal ethics guidelines. 2.4. Vaginal Smears and Estrous Cycle Analysis Daily vaginal smears were collected between 08:00 and 09:00 using 10 μL PBS, fixed in absolute ethanol, and stained with 0.1% crystal violet. Estrous cycle stages, including proestrus, estrus, metestrus, and diestrus, were determined under light microscopy according to the relative proportions of nucleated epithelial cells, cornified epithelial cells, and leukocytes. Cycle regularity was assessed for 13 consecutive days after AAV transduction, starting on day 20. 2.5. H&E Staining and Follicle Counting Ovarian tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned into 5 μm‐thick serial slices for H&E staining. A systematic sampling approach was used to count follicles at different developmental stages according to the morphological criteria [29]: every 10th section from each ovarian tissue block was selected, and primordial, primary, secondary, and antral follicles were counted under a light microscope. The average follicle count per selected section was multiplied by a correction factor of 10 to estimate the total number of follicles in the entire unilateral ovary. 2.6. Serum Hormone Measurement Mouse serum samples were collected by retro‐orbital blood sampling, centrifuged, and stored at −80°C. Levels of estradiol (E2), AMH, and FSH were measured using commercial ELISA kits (RUIXIN Biotech) following the manufacturer's protocols. 2.7. Cell Culture, Reagents, and Cell Transduction The human granulosa cell line KGN was purchased from Procell Life Science & Technology Co. Ltd. (Wuhan, China). Cells were cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum (Gibco, Life Technologies) in a humidified incubator at 37°C with 5% CO2. The KGN cell line retains FSH responsiveness and steroidogenic capacity, serving as a model for reproductive and lipid research. Lentiviral vectors for HILPDA overexpression and empty control lentiviruses, as well as ATGL overexpression plasmids, were obtained from GeneChem. Small interfering RNAs (siRNAs) targeting HILPDA and matched negative control (NC) siRNA were synthesized by Tsingke Biotechnology. Two independent siRNA sequences were designed for HILPDA knockdown, termed siHILPDA#1 and siHILPDA#2. The empty lentiviral vector (Vector) was used as the control for the HILPDA overexpression lentivirus (HILPDA). The knockdown and overexpression efficiencies were verified by Western blotting (WB) and quantitative real‐time PCR (qRT‐PCR). All related sequences and lentiviral vector information are listed in Table S1. The pharmacological reagents Atglistatin (HY‐15859) and Triacsin C (HY‐N6707) were purchased from MedChemExpress. 2.8. RNA Isolation and qRT‐PCR Total RNA was extracted using the RNAkey Kit. Reverse transcription was performed with PrimeScript RT Master Mix (Takara). qRT‐PCR was performed using Hieff SYBR Green Master Mix on an MX3005P thermocycler (Agilent). Relative expression was calculated via the 2−ΔΔCt method with reference gene normalization. Primers are listed in Table S2. 2.9. Western Blotting Analysis Mouse ovarian tissue and KGN cells were lysed in RIPA buffer (Beyotime) supplemented with protease and phosphatase inhibitors. Proteins were separated by SDS‐PAGE, transferred onto PVDF membranes, and immunoblotted with the corresponding primary antibodies (Table S3) at 4°C overnight. HRP‐conjugated secondary antibodies were used for detection via chemiluminescence (Thermo Scientific). Band intensities were quantified with ImageJ. 2.10. Immunohistochemistry (IHC) and Immunofluorescence (IF) For IHC, mouse ovarian sections were incubated with antibodies against HILPDA and EGFP after antigen retrieval. For IF, fixed and permeabilized cells were incubated with antibodies against CHOP and HILPDA, followed by DAPI counterstaining. Images were acquired by confocal microscopy, and staining intensity was quantified using ImageJ. Antibody information is listed in Table S3. 2.11. Cell Proliferation Assays For CCK‐8 assay, KGN cells were seeded at 5 × 103 cells/well and cultured for 24–96 h. Cells were then incubated with CCK‐8 reagent (G1613, Servicebio), and absorbance was measured at 450 nm. For EdU assay, cells were treated with 10 μM EdU (KTA2031, Abbkine), fixed, and stained with Click Reaction solution and Hoechst 33342. EdU‐positive cells were quantified using ImageJ software. 2.12. Apoptosis and Cell Cycle Analysis For apoptosis detection, cells were stained using either the Annexin V‐APC/7‐AAD or Annexin V‐FITC/PI Apoptosis Kit (LiankeBio) following the manufacturer's protocols. For cell cycle analysis, cells were fixed and incubated with DNA staining solution (containing 50 μg/mL propidium iodide and 10 μL permeabilization solution) for 30 min in the dark. Cell apoptosis rates and cell cycle distribution were subsequently determined by flow cytometry. 2.13. Lipid Droplet Staining KGN cells were seeded in 24‐well plates at a density of 1 × 104 cells/well. After fixation, lipid droplets were stained with BODIPY 493/503 (C2053S, Beyotime), and nuclei were counterstained with Hoechst 33342. Fluorescence images were captured using a fluorescence microscope, and BODIPY fluorescence intensity was measured for quantitative analysis. 2.14. Transmission Electron Microscopy (TEM) KGN cells were fixed in 2.5% glutaraldehyde. Samples were processed at the Saiweier Biological TEM platform: ultra‐thin sections were prepared using a Leica EM UC7 ultramicrotome, double‐stained with uranyl acetate and lead citrate, and imaged using an HT7800 transmission electron microscope. Ultrastructural images were captured for intergroup comparative analysis of cellular morphology. 2.15. Mitochondrial Membrane Potential Assay KGN cells were seeded in 96‐well plates and incubated with Mito‐Tracker Red CMXRos (C1999S, Beyotime) at 37°C for 20 min. After washing, cell nuclei were counterstained with Hoechst 33342. Fluorescence images were captured using a fluorescence microscope for quantitative analysis of mitochondrial membrane potential. 2.16. Biochemical and Metabolic Assays For KGN cells, the levels of TG and non‐esterified fatty acid (NEFA) were measured using the TG assay kit (S0219S, Beyotime) and NEFA assay kit (S0215S, Beyotime), respectively. Catalase activity, which reflects cellular reactive oxygen species (ROS) scavenging capacity, was detected using the CAT assay kit (G4307, Servicebio). Intracellular ATP content was determined with the ATP assay kit (PMK1874, Bioprimacy). For human luteinized granulosa cells, NEFA levels were measured using the NEFA assay kit (A042‐1‐1, Nanjing Jiancheng), and ATP levels were detected using the same ATP assay kit (PMK1874, Bioprimacy). The concentration of E2 in the culture supernatant of differently treated KGN cells was measured using the E2 assay kit (PE223, Beyotime). All assays were performed according to the manufacturers' protocols. 2.17. ROS Assay KGN cells were seeded in 24‐well plates and cultured overnight. For ROS detection, cells were incubated with 5 μM CM‐H2DCFDA (S0035S, Beyotime) according to the manufacturer's instructions. After washing, fluorescence images were captured using a fluorescence microscope, and representative images were obtained to compare intracellular ROS levels among groups. 2.18. Broad‐Targeted Lipidomics Analysis KGN cells (1 × 107/sample) were extracted using 80% methanol and methyl tert‐butyl ether (MTBE) with internal standards. The organic phase was collected, dried, redissolved, and analyzed by ultra‐high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC‐QQQ‐MS) on a C18 column. MS detection was performed on a TSQ Altis Plus system in positive and negative electrospray ionization modes using dynamic multiple reaction monitoring. Lipids were quantified using Skyline 22.2.0527 and annotated based on the LIPID MAPS and LION databases. Data repeatability was evaluated using the log2‐transformed coefficient of variation. Three biological replicates per group were analyzed using Student's t‐test or the Wilcoxon rank‐sum test, as appropriate, with false discovery rate (FDR) correction. Orthogonal partial least squares discriminant analysis (OPLS‐DA) was performed, and variable importance in projection (VIP) scores were calculated. Lipids with adjusted p 1.0 were considered differentially abundant. 2.19. Statistical Analysis All data were first tested for normality using the Shapiro–Wilk test. For two‐group comparisons, Student's t‐test was employed for normally distributed data, whereas the Mann–Whitney U test was used for data with a non‐normal distribution. Multiple‐group differences were analyzed via one‐way analysis of variance (ANOVA) followed by Tukey's post hoc test. Correlation analyses were conducted using the Pearson correlation coefficient for normally distributed variables and the Spearman rank correlation coefficient for non‐normally distributed variables. Statistical significance was set at p < 0.05. Statistical analyses were performed using GraphPad Prism 10 and SPSS 27. 3. Results 3.1. Baseline Characteristics A total of 137 young women were enrolled, with inclusion/exclusion criteria detailed in Materials and Methods. Table 1 shows no significant differences in age, body mass index (BMI), basal luteinizing hormone (LH), E2, progesterone (P), total cholesterol (TC), TG, low‐density lipoprotein (LDL), or high‐density lipoprotein (HDL) between groups. Compared to the NOR group, the DOR group had significantly higher basal FSH levels and lower AMH levels, AFC, and oocyte yield. Additionally, normal fertilization rate and embryo formation rate differed between groups. TABLE 1. | Variable | Unit | NOR (n = 70) | DOR (n = 67) | P | |---|---|---|---|---| | Age | Years | 31.00 (28.75–32.25) | 32.00 (29.00–33.00) | 0.121 | | BMI | kg/m2 | 22.70 (20.60–24.57) | 23.70 (20.60–26.40) | 0.080 | | Basal FSH | IU/L | 6.92 (5.36–8.28) | 10.60 (6.40–16.10) | < 0.001* | | Basal LH | IU/L | 5.43 (2.76–8.62) | 4.50 (2.69–6.94) | 0.262 | | Basal E2 | pg/mL | 33.95 (19.07–41.37) | 32.89 (18.90–51.60) | 0.476 | | Basal P | ng/ml | 0.25 (0.17–0.40) | 0.32 (0.18–0.75) | 0.129 | | AMH | ng/L | 4.60 (3.43–8.54) | 0.44 (0.23–0.62) | < 0.001* | | AFC | n | 15.00 (12.00–18.25) | 3.00 (2.00–5.00) | < 0.001* | | Oocyte Yield | n | 7.00 (6.00–8.00) | 2.00 (2.00–4.00) | < 0.001* | | Normal fertilization rate | % | 0.86 (0.75–1.0) | 0.67 (0.50–1.00) | 0.002* | | Embryo formation rate | % | 0.86 (0.78–1.0) | 0.50 (0.00–1.00) | < 0.001* | | TC | mmol/L | 4.30 (3.61–5.00) | 4.15 (3.59–4.88) | 0.345 | | TG | mmol/L | 1.10 (0.73–1.64) | 1.19 (0.83–1.63) | 0.558 | | LDL | mmol/L | 2.62 (2.16–3.20) | 2.45 (1.99–2.94) | 0.332 | | HDL | mmol/L | 1.43 (1.16–1.69) | 1.40 (1.10–1.66) | 0.619 | Note: Median (Interquartile range). p < 0.05. 3.2. Aberrant HILPDA Expression in GCs Is Associated With the Clinical Characteristics of DOR We initially examined HILPDA expression in GCs using our previously published RNA‐seq dataset of DOR and NOR patients [18]. This analysis revealed markedly elevated HILPDA expression in the DOR group compared with the NOR group (Figure 1A), suggesting a potential link to DOR pathogenesis. We further validated this observation by qRT‐PCR in a validation subset of 64 participants, which confirmed consistent upregulation of HILPDA mRNA in DOR GCs (Figure 1B). Correspondingly, IF staining showed increased HILPDA fluorescence intensity in GCs from the DOR group (Figure 1C). Given that GC apoptosis and metabolic homeostasis are essential for maintaining ovarian reserve, we next assessed apoptosis levels and intracellular ATP and NEFA concentrations. Flow cytometry demonstrated an increased apoptotic rate in DOR GCs (Figure 1D), while ATP and NEFA levels were reduced (Figure 1E,F). To further clarify the clinical significance of HILPDA upregulation, we analyzed its correlations with key reproductive parameters and ART outcomes. HILPDA mRNA expression showed no significant association with BMI, E2, LH, or P, but was positively correlated with basal FSH (r = 0.3662) and negatively correlated with AMH (r = −0.4483) and AFC (r = −0.4347). Regarding ART outcomes, HILPDA mRNA expression was inversely associated with oocyte yield (r = −0.3606) and normal fertilization rate (r = −0.2740), whereas no correlation was detected with embryo formation rate (Figures 1G and S1). Collectively, these results indicate that HILPDA upregulation in GCs is associated with DOR and adverse reproductive outcomes. 3.3. HILPDA Overexpression Promotes Follicular Atresia and Estrous Cycle Disorder In vivo, we established a HILPDA‐overexpressing mouse model via ovarian in situ injection to investigate its effect on follicular development (Figure 2A). Mice were injected with pAAV‐CAG‐HILPDA‐P2A‐EGFP (HILPDA) or the control vector pAAV‐CAG‐EGFP (Vector); uninjected mice served as an additional control. Successful transduction was initially confirmed by IHC for EGFP (Figure S2A). H&E staining revealed a significant increase in the number of atretic follicles in the HILPDA group (Figure 2B,C). Elevated HILPDA expression was validated by qRT‐PCR (Figure 2D), WB (Figure 2E,F), and IHC (Figure 2G). Body weight and ovarian index were comparable between groups (Figure S2B,C). HILPDA overexpression disrupted the estrous cycle, with prolonged proestrus and shortened estrus (Figure 2H,I). The hormonal profile indicated diminished ovarian reserve, including significantly increased FSH and trends toward reduced AMH and altered E2 (Figure 2J–L). These results indicate that HILPDA overexpression may disrupt follicular homeostasis and impair ovarian function. 3.4. HILPDA Modulates KGN Cell Proliferation, Apoptosis, and Cell Cycle Progression To explore the biological function of HILPDA in human GCs, we adopted KGN cells, a classic in vitro model for GC‐related research, to conduct gain‐ and loss‐of‐function assays. We first confirmed the satisfactory overexpression and knockdown efficiency of HILPDA at both mRNA and protein levels (Figure 3A,E). CCK‐8 and EdU results demonstrated that HILPDA overexpression markedly inhibited cell viability and proliferation (Figures 3B and S3A). Flow cytometry cell cycle assays demonstrated that HILPDA overexpression caused S‐phase arrest and a decline in G2/M cell population (Figure S3B), indicative of stalled DNA replication. Meanwhile, increased apoptosis was detected in the HILPDA overexpression group (Figure 3C). WB analysis further confirmed the downregulation of Cyclin A2 and Bcl‐2, as well as the upregulation of p21 and Bax under HILPDA overexpression (Figure 3D). As expected, HILPDA silencing produced the opposite phenotypic and molecular changes (Figures 3F–H and S3C,D). These results indicate that HILPDA may play a detrimental role in GC physiological maintenance. 3.5. HILPDA Induces Lipid Droplet Deposition and Global Lipidomic Remodeling Given the role of HILPDA, we combined BODIPY staining with broad‐targeted lipidomics to explore its metabolic function in GCs. BODIPY signals revealed increased lipid droplet deposition upon HILPDA overexpression and reduced lipid droplets following HILPDA knockdown (Figure 4A,F), suggestive of abnormal lipid storage. We further performed broad‐targeted lipidomics to systematically profile lipid changes. A total of 1084 lipid species were annotated, covering glycerophospholipids, sphingolipids, fatty acyls, glycerolipids, sterol lipids and prenol lipids (Figure 4B). Pearson correlation analysis and OPLS‐DA revealed distinct lipidomic profiles between vector group and HILPDA overexpression group (Figure S4). Differential analysis identified 162 significantly upregulated lipids and 129 downregulated lipids (Figure 4C). Notably, TG levels were markedly elevated, whereas key membrane and signaling lipids, including lysophosphatidylcholine (LPC), phosphatidylcholine (PC), cardiolipin (CL), phosphatidylserine, phosphatidylinositol, as well as specific cholesteryl esters (CEs) and fatty acids (FAs), were substantially depleted (Figure 4D). LION enrichment analysis further indicated a pronounced shift in the cellular lipid equilibrium toward esterification and storage (Figure 4E). Biochemical assays confirmed elevated intracellular TG and reduced NEFA levels upon HILPDA overexpression, whereas the opposite phenotype occurred upon HILPDA knockdown (Figure 4G). Furthermore, WB analysis was performed to detect lipid metabolic regulators [30]. Diacylglycerol O‐acyltransferase 1 (DGAT1), perilipin 1 (PLIN1), and cell death‐inducing DFFA‐like effector C (CIDEC) are important lipogenic mediators involved in lipid synthesis and lipid droplet formation, whereas ATGL functions as a principal lipolytic enzyme [31]. HILPDA overexpression significantly upregulated the levels of these lipogenic proteins and repressed ATGL expression; conversely, HILPDA knockdown produced the opposite effects (Figure 4H). Because the depletion of phospholipids and CL can disrupt mitochondrial and ER membrane architecture, and reduced CE availability may limit steroidogenic substrate supply, we next investigated whether HILPDA‐mediated lipid redistribution impairs E2 production, mitochondrial function, and ER proteostasis. 3.6. HILPDA‐Induced Lipid Dysregulation Impairs Steroidogenesis and Triggers Mitochondrial Dysfunction and ER Stress Based on our lipidomic data, we observed widespread reduction in CE abundance following HILPDA overexpression (Figure 5A). We next determined the expression profiles of steroidogenic genes, including sterol regulatory element‐binding transcription factor 1 (SREBF1), SREBP cleavage‐activating protein (SCAP), StAR‐related lipid transfer domain‐containing protein 5 (STARD5) [32], as well as steroidogenic enzymes HSD3B and CYP19A1 [33]. qRT‐PCR results showed that HILPDA overexpression significantly altered the transcription of STARD5, HSD3B1, HSD3B2, and CYP19A1, and such transcriptional changes were fully rescued by HILPDA knockdown (Figure 5B). In line with altered steroidogenic gene expression, cellular E2 secretion was notably reduced upon HILPDA overexpression (Figure 5C). Apart from impaired steroidogenesis, CL depletion caused by HILPDA overexpression suggested potential damage to inner mitochondrial membrane structure and function. TEM showed aberrant mitochondrial morphology and massive lipid droplet accumulation in HILPDA overexpression cells. HILPDA overexpression also suppressed the phosphorylation of LKB1 and AMPK (Figure S5A–C). MitoTracker Red CMXRos fluorescence decreased upon HILPDA overexpression, whereas HILPDA knockdown produced an opposite phenotype (Figure 5D). Analysis of genes related to mitochondrial dynamics [34] showed upregulation of the fission‐related gene DRP1 and downregulation of fusion‐related genes (OPA1, MFN1, MFN2; Figure 5E). Accompanied by mitochondrial structural and functional damage, intracellular ATP levels were markedly reduced (Figure 5F). HILPDA overexpression also elevated cellular ROS content, with increased hydrogen peroxide (H2O2) validated via quantitative measurement and fluorescence staining (Figures 5G and S5D). Conversely, the opposite phenotype was observed following HILPDA knockdown. We next examined ER stress status in GCs. WB revealed increased GRP78 and CHOP levels upon HILPDA overexpression, while opposite trends were observed in HILPDA knockdown cells. Among the three canonical unfolded protein response pathways, the ATF6 pathway and the eIF2α‐ATF4 arm were significantly activated, whereas the IRE1α‐XBP1s pathway showed no significant change (Figure 5H). IF staining also revealed increased nuclear accumulation of CHOP in HILPDA overexpression cells (Figure S5E). Taken together, these data suggest that aberrant lipid metabolism driven by HILPDA suppresses steroidogenesis, induces mitochondrial dysfunction and oxidative stress, and triggers ER stress, eventually disturbing the homeostasis of GCs. 3.7. Restoration of Lipolysis or Inhibition of Excessive Lipid Droplet Formation Alleviates HILPDA‐Induced Lipotoxicity and Cellular Dysfunction Given the above, we reasoned that restoring lipid metabolic homeostasis could alleviate HILPDA‐induced lipotoxicity. To test this, we performed genetic rescue experiments combined with pharmacological intervention. Accumulating studies have revealed that HILPDA directly regulates ATGL by suppressing its enzymatic activity and reducing its protein abundance [22, 23]. Accordingly, we employed ATGL genetic rescue, along with pharmacological inhibition using Atglistatin (ATGL inhibitor, 10 μM) [35] and Triacsin C (long‐chain acyl‐CoA synthetase inhibitor that suppresses lipid droplet accumulation, 5 μM) [36]. We overexpressed ATGL in HILPDA overexpression KGN cells, and successful transfection was verified at both the mRNA and protein levels (Figure S6A). HILPDA overexpression cells were treated with Triacsin C or Atglistatin, and Atglistatin was also administered to HILPDA knockdown cells. Biochemical quantification revealed that ATGL rescue markedly reduced intracellular TG accumulation and lipid droplet abundance in HILPDA overexpression cells (Figure 6A,B). Atglistatin further increased TG levels in both HILPDA overexpression and knockdown cells, whereas Triacsin C alleviated lipid deposition in HILPDA overexpression cells. NEFA levels exhibited an opposite trend to TG across all treatment groups (Figure 6C). Subsequently, we evaluated mitochondrial function among different groups. ATGL restoration increased ATP levels and restored MitoTracker Red CMXRos fluorescence in HILPDA‐overexpressing cells. Consistently, Triacsin C treatment increased ATP levels in HILPDA overexpression cells, whereas Atglistatin further decreased their ATP content (Figure 6D,E). Notably, cellular oxidative stress levels exhibited an opposite variation trend relative to ATP content across all treatment groups (Figure 6F). Moreover, ATGL restoration also mitigated ER stress (Figure 6G), recovered proliferative capacity (Figure S6B), decreased apoptosis (Figure 6H), and decreased nuclear accumulation of CHOP (Figure S6C). Restoration of lipolysis or suppression of excessive lipid droplet accumulation effectively rescued the impaired E2 secretion induced by HILPDA overexpression (Figure 6I). These results support the conclusion that restoring ATGL‐mediated lipolysis or limiting lipid esterification alleviates HILPDA‐associated lipid accumulation and cellular dysfunction. 4. Discussion DOR represents an important concern in female reproductive health because it not only reflects premature aging of the female reproductive system but also compromises ART outcomes and embryo quality [37]. Our work identifies HILPDA as a potential pathogenic mediator in DOR and provides mechanistic evidence linking HILPDA‐associated lipid dysregulation to GC dysfunction. HILPDA is markedly upregulated in GCs from DOR patients, correlating with reduced ovarian reserve and poor ART outcomes. Ovarian HILPDA overexpression promoted follicular atresia and estrous cycle disturbance in mice, whereas HILPDA overexpression in KGN cells inhibited proliferation and triggered apoptosis. Mechanistically, lipidomic profiling revealed a distinct pattern of lipid remodeling characterized by TG‐rich lipid droplet accumulation, accompanied by depletion of phospholipids, CEs, and CL. This lipid redistribution was associated with impaired estradiol biosynthesis, mitochondrial dysfunction, and ER stress activation (Figure 7). Importantly, restoration of lipolysis or inhibition of excessive lipid droplet formation alleviated HILPDA‐associated lipotoxicity and cellular dysfunction in GCs. HILPDA, a well‐characterized regulator of lipid droplet biogenesis, has been primarily studied in cancer cell survival, hepatic steatosis, and macrophage lipid handling [20, 21, 22, 23, 24, 25, 26, 27]. Nevertheless, excessive lipid droplet accumulation may exert detrimental biological effects. Previous studies have reported lipid droplet accumulation and mitochondrial ultrastructural abnormalities in ovarian tissues from mice exposed to environmental pollutants, including cadmium, as well as in KGN cells, suggesting a potential link between aberrant lipid deposition and ovarian cell dysfunction [38, 39]. In addition, a transgenic reporter mouse model expressing mCherry‐fused HPos, a specific peptide labeling nascent lipid droplets, has been established for tracing ovarian lipid droplet biogenesis, in which excessive lipid droplet deposition was detected in atretic follicles, implying that aberrant lipid droplet overaccumulation is potentially detrimental [40]. To our knowledge, our findings provide the first evidence linking HILPDA‐driven lipidomic dysregulation to a pathological “lipid sequestration”‐like state in GCs, in which lipid resources appear to be preferentially redistributed toward TG‐rich lipid droplets at the expense of other essential lipid pools. This lipid redistribution carries profound functional consequences. CEs serve as intracellular cholesterol reservoirs that can provide cholesterol for steroid hormone synthesis in GCs [41]. As the predominant cellular source of ovarian E2, GCs rely on cholesterol substrates, as well as mitochondrial energy supply and endoplasmic reticulum‐associated enzymatic conditions, to maintain normal steroidogenic capacity [42]. Therefore, altered CE abundance may reflect disrupted intracellular cholesterol storage and may be associated with impaired estradiol biosynthesis. Mitochondria are known to be intimately associated with ovarian function and reproductive longevity [43]. Mitochondria continuously undergo dynamic fission and fusion to maintain normal structure and function [34]. CL is a signature phospholipid highly enriched in the inner mitochondrial membrane, where it contributes to cristae architecture, respiratory chain supercomplex stability, and oxidative phosphorylation [44, 45, 46, 47]. In line with this notion, HILPDA overexpression was associated with reduced mitochondrial membrane potential, decreased ATP production, disturbed mitochondrial dynamics, and increased ROS generation. Moreover, PC, as a major structural lipid of the ER membrane, together with LPC‐related membrane lipid remodeling, contributes to ER homeostasis, while the ER also participates in the regulation of mitochondria‐dependent apoptosis [48]. PC insufficiency and LPC‐related membrane lipid remodeling, together with mitochondrial ROS overproduction, appear to exacerbate ER membrane stress and promote activation of the unfolded protein response [49], as indicated by GRP78 induction and increased nuclear accumulation of CHOP. This mitochondrial‐ER stress crosstalk, potentially reinforced by upstream lipid sequestration defects, may represent a pathogenic cascade contributing to GC apoptosis and follicular atresia in DOR. Although GCs are inherently hypoxia‐sensitive, and hypoxia‐inducible factors act as well‐characterized upstream regulators of HILPDA expression [50], our study does not directly clarify whether aberrant HILPDA upregulation in DOR GCs arises from the local hypoxic microenvironment. In fact, follicular senescence‐related metabolic stress, disrupted local hypoxic conditions, and dysregulated hormonal signaling pathways may all act as potential inducers of elevated HILPDA expression. Genetic rescue assays and pharmacological interventions supported the functional role of the HILPDA‐ATGL regulatory axis, yet the endogenous protein interaction between them has not been validated in GCs. In vivo validation was limited to HILPDA overexpression models, and complementary loss‐of‐function animal experiments are still needed to determine whether endogenous HILPDA is required for DOR pathogenesis. In addition, mitochondrial dysfunction was assessed mainly using indirect functional and structural indicators rather than comprehensive bioenergetic assays, and the causal contribution of ER stress to GC apoptosis remains to be further defined. In summary, our findings suggest that HILPDA may contribute to GC dysfunction in DOR by reshaping lipid metabolism toward excessive TG‐rich lipid droplet accumulation and concomitant depletion of structural and functional lipid pools. This lipid remodeling is associated with impaired steroidogenic capacity, mitochondrial dysfunction, ER stress activation, and increased follicular atresia. Importantly, restoration of lipid turnover or suppression of excessive lipid droplet formation mitigated HILPDA‐associated lipotoxicity and cellular dysfunction, highlighting the maintenance of lipid homeostasis as a potential therapeutic strategy for preserving ovarian reserve in DOR. Author Contributions Xiaolei Liang designed and supervised the study. Xing Ma conducted the validation experiments and prepared the figures and tables. Yajuan Li helped collect the clinical samples. Liangjian Ma and Yue Liu helped with the animal experiments. Xing Ma wrote the original manuscript with inputs from all co‐authors. Hongli Li and Chang Liu helped edit and revise the manuscript. All the authors read the manuscript and approved the final version. Funding This work was funded by the National Natural Science Foundation of China (No. 82360303), Gansu Provincial key research and development project (No. 24YFFA038), The Science and Technology Innovation Major Project of the Health Commission of Gansu Province (No. GSWSZD2025‐03), Lanzhou University Outstanding Youth Program (No. lzujbky‐2024‐oy08), Gansu Province Graduate Innovation Funding Project (No. 2026CXZX‐113). Ethics Statement The study involving human participants was reviewed and approved by the Independent Review Board of The First Hospital of Lanzhou University (Ethics number: LDYYLL2025‐272). All participants provided written informed consent prior to enrollment. The research was conducted in accordance with the Declaration of Helsinki. Animal Studies: The project was approved by the ethics committee of the First Hospital of Lanzhou University (Ethics number: LDYYLL2025‐456). Conflicts of Interest The authors declare no conflicts of interest. Supporting information Acknowledgments We thank Gansu Provincial Clinical Research Center for Gynecological Oncology, Branch of National Clinical Research Center for Gynecology and Obstetrics for their support. Data Availability Statement All the data and experimental details in this article may be obtained from the corresponding author upon reasonable request.

- 1. Dogan S., Cicek O. S. Y., Demir M., et al., “The Effect of Growth Hormone Adjuvant Therapy on Assisted Reproductive Technologies Outcomes in Patients With Diminished Ovarian Reserve or Poor Ovarian Response,” Journal of Gynecology Obstetrics and Human Reproduction 50, no. 2 (2021): 101982. [DOI] [PubMed] [Google Scholar] - 2. Jiao Z. and Bukulmez O., “Potential Roles of Experimental Reproductive Technologies in Infertile Women With Diminished Ovarian Reserve,” Journal of Assisted Reproduction and Genetics 38, no. 10 (2021): 2507–2517. [DOI] [PMC free article] [PubMed] [Google Scholar] - 3. La Marca A. and Diamanti M., “Factors Affecting Age at Menopause and Their Relationship With Ovarian Reserve: A Comprehensive Review,” European Journal of Contraception & Reproductive Health Care 29, no. 5 (2024): 245–255. [DOI] [PubMed] [Google Scholar] - 4. Jiang L., Yang S., and Zhang C., “Sigma‐1 Receptor‐Mediated High Mobility Group a1 Silencing Alleviates Endoplasmic Reticulum Stress‐Induced Ovarian Granulosa Cell Apoptosis: An In Vitro Cell Experimental Study,” BJOG: An International Journal of Obstetrics and Gynaecology 132, no. Suppl 2 (2025): 120–131. [DOI] [PubMed] [Google Scholar] - 5. Chen Y., Zhao Y., Miao C., et al., “Quercetin Alleviates Cyclophosphamide‐Induced Premature Ovarian Insufficiency in Mice by Reducing Mitochondrial Oxidative Stress and Pyroptosis in Granulosa Cells,” Journal of Ovarian Research 15, no. 1 (2022): 138. [DOI] [PMC free article] [PubMed] [Google Scholar] - 6. Huang Y., Cheng Y., Zhang M., et al., “Oxidative Stress and Inflammatory Markers in Ovarian Follicular Fluid of Women With Diminished Ovarian Reserve During In Vitro Fertilization,” Journal of Ovarian Research 16, no. 1 (2023): 206. [DOI] [PMC free article] [PubMed] [Google Scholar] - 7. Luo J., Qin Y., Zhu Y., et al., “Electroacupuncture Improves Ovarian Function in Rats With Tripterygium Glycoside‐Induced Diminished Ovarian Reserve by Promoting the Polarization of m2 Macrophages and Inhibiting Inflammatory Responses,” Mediators of Inflammation 2025 (2025): 1694470. [DOI] [PMC free article] [PubMed] [Google Scholar] - 8. Zeng Y., Wang C., Yang C., et al., “Unveiling the Role of Chronic Inflammation in Ovarian Aging: Insights Into Mechanisms and Clinical Implications,” Human Reproduction 39, no. 8 (2024): 1599–1607. [DOI] [PubMed] [Google Scholar] - 9. Zhao Z., Fan Q., Zhu Q., et al., “Decreased Fatty Acids Induced Granulosa Cell Apoptosis in Patients With Diminished Ovarian Reserve,” Journal of Assisted Reproduction and Genetics 39, no. 5 (2022): 1105–1114. [DOI] [PMC free article] [PubMed] [Google Scholar] - 10. Liang J., Huang F., Hao X., et al., “Nicotinamide Mononucleotide Supplementation Rescues Mitochondrial and Energy Metabolism Functions and Ameliorates Inflammatory States in the Ovaries of Aging Mice,” MedComm (2020) 5, no. 10 (2024): e727. [DOI] [PMC free article] [PubMed] [Google Scholar] - 11. Ferraretti A. P., La Marca A., Fauser B. C., et al., “ESHRE Consensus on the Definition of ‘Poor Response’ to Ovarian Stimulation for In Vitro Fertilization: The Bologna Criteria,” Human Reproduction 26, no. 7 (2011): 1616–1624. [DOI] [PubMed] [Google Scholar] - 12. Alviggi C., Andersen C. Y., Buehler K., et al., “A New More Detailed Stratification of Low Responders to Ovarian Stimulation: From a Poor Ovarian Response to a Low Prognosis Concept,” Fertility and Sterility 105, no. 6 (2016): 1452–1453. [DOI] [PubMed] [Google Scholar] - 13. Osman N. A. and Morgham A. E., “Update on Assessment of Ovarian Reserve Testing,” Obstetrical & Gynecological Survey 79, no. 7 (2024): 429–435. [DOI] [PubMed] [Google Scholar] - 14. Sirait B., Wiweko B., Jusuf A. A., et al., “Oocyte Competence Biomarkers Associated With Oocyte Maturation: A Review,” Frontiers in Cell and Developmental Biology 9 (2021): 710292. [DOI] [PMC free article] [PubMed] [Google Scholar] - 15. Zhang C.‐H., Liu X.‐Y., and Wang J., “Essential Role of Granulosa Cell Glucose and Lipid Metabolism on Oocytes and the Potential Metabolic Imbalance in Polycystic Ovary Syndrome,” International Journal of Molecular Sciences 24, no. 22 (2023): 16247. [DOI] [PMC free article] [PubMed] [Google Scholar] - 16. Liu T., Qu J., Tian M., et al., “Lipid Metabolic Process Involved in Oocyte Maturation During Folliculogenesis,” Frontiers in Cell and Developmental Biology 10 (2022): 806890. [DOI] [PMC free article] [PubMed] [Google Scholar] - 17. Blengini C. S. and Schindler K., “Follicular Communication Breakdown in Aging Ovaries,” Nature Aging 3, no. 6 (2023): 636–637. [DOI] [PubMed] [Google Scholar] - 18. Zhu Q., Du J., Li Y., et al., “Downregulation of Glucose‐Energy Metabolism via AMPK Signaling Pathway in Granulosa Cells of Diminished Ovarian Reserve Patients,” Gene 933 (2025): 148979. [DOI] [PubMed] [Google Scholar] - 19. Yang X., Zhao Z., Fan Q., et al., “Cholesterol Metabolism is Decreased in Patients With Diminished Ovarian Reserve,” Reproductive Biomedicine Online 44, no. 1 (2022): 185–192. [DOI] [PubMed] [Google Scholar] - 20. VandeKopple M. J., Wu J., Auer E. N., et al., “HILPDA Regulates Lipid Metabolism, Lipid Droplet Abundance, and Response to Microenvironmental Stress in Solid Tumors,” Molecular Cancer Research 17, no. 10 (2019): 2089–2101. [DOI] [PMC free article] [PubMed] [Google Scholar] - 21. Kulminskaya N. and Oberer M., “Protein–Protein Interactions Regulate the Activity of Adipose Triglyceride Lipase in Intracellular Lipolysis,” Biochimie 169, no. 62–68 (2020): 62–68. [DOI] [PubMed] [Google Scholar] - 22. Padmanabha Das K. M., Wechselberger L., Liziczai M., et al., “Hypoxia‐Inducible Lipid Droplet‐Associated Protein Inhibits Adipose Triglyceride Lipase,” Journal of Lipid Research 59, no. 3 (2018): 531–541. [DOI] [PMC free article] [PubMed] [Google Scholar] - 23. de la Rosa Rodriguez M. A. and Kersten S., “Regulation of Lipid Droplet Homeostasis by Hypoxia Inducible Lipid Droplet Associated HILPDA,” Biochimica et Biophysica Acta, Molecular and Cell Biology of Lipids 1865, no. 9 (2020): 158738. [DOI] [PubMed] [Google Scholar] - 24. Deng L., Wu S. A., Qi L., et al., “HILPDA is a Lipotoxic Marker in Adipocytes That Mediates the Autocrine Negative Feedback Regulation of Triglyceride Hydrolysis by Fatty Acids and Alleviates Cellular Lipotoxic Stress,” Molecular Metabolism 75 (2023): 101773. [DOI] [PMC free article] [PubMed] [Google Scholar] - 25. Zhang X., Saarinen A. M., Hitosugi T., et al., “Inhibition of Intracellular Lipolysis Promotes Human Cancer Cell Adaptation to Hypoxia,” eLife 6 (2017): e31132. [DOI] [PMC free article] [PubMed] [Google Scholar] - 26. Povero D., Chen Y., Johnson S. M., et al., “HILPDA Promotes NASH‐Driven HCC Development by Restraining Intracellular Fatty Acid Flux in Hypoxia,” Journal of Hepatology 79, no. 2 (2023): 378–393. [DOI] [PMC free article] [PubMed] [Google Scholar] - 27. Sheng Y., Li J., Yang Y., et al., “Hypoxia‐Inducible Lipid Droplet‐Associated (HILPDA) Facilitates the Malignant Phenotype of Lung Adenocarcinoma Cells In Vitro Through Modulating Cell Cycle Pathways,” Tissue & Cell 70, no. 101495 (2021): 101495. [DOI] [PubMed] [Google Scholar] - 28. Liu L., Liu T., Jia R., et al., “Downregulation of Fatty Acid Oxidation Led by Hilpda Increases G2/M Arrest/Delay‐Induced Kidney Fibrosis,” Biochimica et Biophysica Acta‐Molecular Basis of Disease 1869, no. 5 (2023): 166701. [DOI] [PubMed] [Google Scholar] - 29. Myers M., Britt K. L., Wreford N. G., et al., “Methods for Quantifying Follicular Numbers Within the Mouse Ovary,” Reproduction 127, no. 5 (2004): 569–580. [DOI] [PubMed] [Google Scholar] - 30. Cui L. and Liu P., “Two Types of Contact Between Lipid Droplets and Mitochondria,” Frontiers in Cell and Developmental Biology 8 (2020): 618322. [DOI] [PMC free article] [PubMed] [Google Scholar] - 31. Ganeva I., Lim K., Boulanger J., et al., “The Architecture of Cidec‐Mediated Interfaces Between Lipid Droplets,” Cell Reports 42, no. 2 (2023): 112107. [DOI] [PMC free article] [PubMed] [Google Scholar] - 32. Galano M., Venugopal S., and Papadopoulos V., “Role of STAR and SCP2/SCPx in the Transport of Cholesterol and Other Lipids,” International Journal of Molecular Sciences 23, no. 20 (2022): 12115. [DOI] [PMC free article] [PubMed] [Google Scholar] - 33. Kabakci R., Clark K. L., Plewes M. R., et al., “Perfluorooctanoic Acid (PFOA) Inhibits Steroidogenesis and Mitochondrial Function in Bovine Granulosa Cells In Vitro,” Environmental Pollution 338, no. 122698 (2023): 122698. [DOI] [PMC free article] [PubMed] [Google Scholar] - 34. Al Ojaimi M., Salah A., and El‐Hattab A. W., “Mitochondrial Fission and Fusion: Molecular Mechanisms, Biological Functions, and Related Disorders,” Membranes 12, no. 9 (2022): 893. [DOI] [PMC free article] [PubMed] [Google Scholar] - 35. Tan Y., Huang Z., Jin Y., et al., “Lipid Droplets Sequester Palmitic Acid to Disrupt Endothelial Ciliation and Exacerbate Atherosclerosis in Male Mice,” Nature Communications 15, no. 1 (2024): 8273. [DOI] [PMC free article] [PubMed] [Google Scholar] - 36. Shen Z., Qi Y., Chu M., et al., “FABP4‐Mediated Lipid Droplet Accumulation Drives Epithelial‐Mesenchymal Transition and Aggravates Alveolar Epithelial Barrier Disruption,” Clinical and Translational Medicine 16, no. 1 (2026): e70563. [DOI] [PMC free article] [PubMed] [Google Scholar] - 37. Zhu Q., Li Y., Ma J., et al., “Potential Factors Result in Diminished Ovarian Reserve: A Comprehensive Review,” Journal of Ovarian Research 16, no. 1 (2023): 208. [DOI] [PMC free article] [PubMed] [Google Scholar] - 38. Zhang Y., Zhou J., Zeng L., et al., “Paternal Cadmium Exposure Affects Estradiol Synthesis by Impairing Intracellular Cholesterol Homeostasis and Mitochondrial Function in Offspring Female Mice,” Ecotoxicology and Environmental Safety 263 (2023): 115280. [DOI] [PubMed] [Google Scholar] - 39. Zhang Y., Hales B. F., and Robaire B., “Exposure to Polystyrene Nanoplastics Induces Lysosomal Enlargement and Lipid Droplet Accumulation in KGN Human Ovarian Granulosa Cells,” Archives of Toxicology 99, no. 4 (2025): 1445–1454. [DOI] [PubMed] [Google Scholar] - 40. Ibayashi M., Aizawa R., Mitsui J., et al., “Lipid Droplet Synthesis Is Associated With Angiogenesis in Mouse Ovarian Follicles†,” Biology of Reproduction 108, no. 3 (2023): 492–503. [DOI] [PubMed] [Google Scholar] - 41. Wang X., Lee E., Hales B. F., et al., “Organophosphate Esters Disrupt Steroidogenesis in Kgn Human Ovarian Granulosa Cells,” Endocrinology 164, no. 7 (2023): bqad089. [DOI] [PMC free article] [PubMed] [Google Scholar] - 42. Zhang S., Guo B., Fang J., et al., “Abnormal Cholesterol‐Cholesteryl Ester Metabolism Impairs Mouse Oocyte Quality During Ovarian Aging,” Cellular & Molecular Biology Letters 30, no. 1 (2025): 140. [DOI] [PMC free article] [PubMed] [Google Scholar] - 43. Mani S., Srivastava V., Shandilya C., et al., “Mitochondria: The Epigenetic Regulators of Ovarian Aging and Longevity,” Frontiers in Endocrinology (Lausanne) 15 (2024): 1424826. [DOI] [PMC free article] [PubMed] [Google Scholar] - 44. Jiang Z., Shen T., Huynh H., et al., “Cardiolipin Regulates Mitochondrial Ultrastructure and Function in Mammalian Cells,” Genes (Basel) 13, no. 10 (2022): 1889. [DOI] [PMC free article] [PubMed] [Google Scholar] - 45. Venkatraman K., Lee C. T., and Budin I., “Setting the Curve: The Biophysical Properties of Lipids in Mitochondrial Form and Function,” Journal of Lipid Research 65, no. 10 (2024): 100643. [DOI] [PMC free article] [PubMed] [Google Scholar] - 46. Sych T., Levental K. R., and Sezgin E., “Lipid–Protein Interactions in Plasma Membrane Organization and Function,” Annual Review of Biophysics 51 (2022): 135–156. [DOI] [PMC free article] [PubMed] [Google Scholar] - 47. Palma F. R., Gantner B. N., Sakiyama M. J., et al., “ROS Production by Mitochondria: Function or Dysfunction?,” Oncogene 43, no. 5 (2024): 295–303. [DOI] [PubMed] [Google Scholar] - 48. Jauch A. T., Sailer J., Braun J., et al., “Neocarzilin A Induces Apoptosis and Mitochondrial Disturbance by Targeting Reticulon 4‐Mediated Endoplasmic Reticulum Stress,” Cell Death Discovery 11, no. 1 (2025): 278. [DOI] [PMC free article] [PubMed] [Google Scholar] - 49. Jiang L., Cui J., Zhang C., et al., “Sigma‐1 Receptor Is Involved in Diminished Ovarian Reserve Possibly by Influencing Endoplasmic Reticulum Stress‐Mediated Granulosa Cells Apoptosis,” Aging (Albany NY) 12, no. 10 (2020): 9041–9065. [DOI] [PMC free article] [PubMed] [Google Scholar] - 50. Zhang L., Liu K., Liu Z., et al., “In Pre‐Clinical Study Fetal Hypoxia Caused Autophagy and Mitochondrial Impairment in Ovary Granulosa Cells Mitigated by Melatonin Supplement,” Journal of Advanced Research 64 (2024): 15–30. [DOI] [PMC free article] [PubMed] [Google Scholar] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Data Availability Statement All the data and experimental details in this article may be obtained from the corresponding author upon reasonable request.