Obesity May Impairs Mice Testicular Structure by STAT3/CYP19A1/Testosterone

Research Article

Austin J Endocrinol Diabetes. 2023; 10(1): 1101.

Obesity May Impairs Mice Testicular Structure by STAT3/CYP19A1/Testosterone

Mengnan Lu¹; Ruoyang Feng²; Yanfeng Xiao¹*; Chunyan Yin¹*

¹Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao tong University, China

²Department of Joint Surgery, HongHui Hospital, Xi’an Jiao tong University, China

*Corresponding author: Yanfeng Xiao Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao tong University, China.

Chunyan Yin Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao tong University, China Email: [email protected]

Received: July 10, 2023 Accepted: August 16, 2023 Published: August 23, 2023


Obesity is an increasing serious global public health issue and a risk factor for male infertility. Aromatase expression level is elevated in obese men, and this high level is as-sociated with diminished serum testosterone levels. We explored the underlying mechanism of infertility in obese men. Genome-wide association study datasets were used to predict the causal relationship between obesity and male infertility. An obese male mouse model was generated by feeding mice a high-fat diet while control model was generated by feeding mice a normal chow diet. Serum indicators including free fatty acids, insulin, Follicle-stimulating hormone, and testosterone were measured using ELISA, and impaired fertility in mice was demonstrated using immunohistochemistry. The expression levels of STAT3 and CYP19A1 were measured by RT-qPCR and western blotting, respectively. Simultaneous bioinformatics analysis of publicly available data was performed using the R programming language and JASPAR database. Obesity might lead to male infertility from a genomic perspective. Obese mice displayed reduced serum testosterone and follicle stimulating hormone levels along with structural abnormalities, ectopic lipid deposition, and chronic inflammation in the testes. Upregulation of STAT3/CYP19A1 expression in obese mice was linked to reduced serum testosterone levels and impaired fertility. Our observation may support the hypothesis that since the elevation of STAT3 expression in obesity, the promoted expressed CYP19A1 could increase a shift from testosterone to estrogens. The persistently elevated level of estrogen will further stimulate STAT3, which may constitute a positive feedback loop. These findings provide new insights into the mechanisms of obesity-mediated male fertility impairment.

Keywords: STAT3; CYP19A1; Testosterone; Obesity; Male fertility impairment


Obesity is an increasingly serious global public health issue [1]. The prevalence of obesity in children has increased rapidly [2]. Rising global obesity in childhood has profound implications, including obesity in adulthood, nonalcoholic fatty liver disease, type 2 diabetes, cardiometabolic disease, sleep apnea syndrome, and other conditions [3]. Childhood and adolescence are critical periods of growth and development, and childhood obesity is associated with penile and testicular dysplasia [4]. Compared to healthy controls, obese adolescents display significantly higher body mass index (BMI; 27.1±2.2 kg/m2, P<0.05), shorter natural penile length (5.6±1.7 cm, P<0.05), smaller testicular volume (7.6±2.3 cm3, P<0.05), and lower level of spermatogenesis (chi2 = 17.335, P<0.05) [5]. Epidemiological studies have provided some clear evidence that obesity impacts negatively on male fertility [6]. A cross-sectional study of 4400 infertile men in the United States has reported a significant negative association between obesity and semen parameters. The authors also noted that the occurrence of azoospermia and oligospermia was more prevalent in obese men [7].

Whether obesity affects male fertility potential is unclear, with some studies suggesting that BMI is not related to the quality of sperm parameters [8], while others suggest that obesity affects semen quality to some extent [9]. Obesity may diminish male fertility and reproductive potential, and it is associated with erectile dysfunction, poor semen quality, subclinical prostatitis, and other deleterious conditions [10]. High circulating levels of leptin is one of characterizing feature of obesity, which is associated with low testosterone in men [11]. Although it might be explained that the imbalanced leptin levels increase the aromatase activity, studies are needed to establish the molecular mechanism between leptin and testosterone in obese men. Male infertility is a major global health problem. However, the mechanisms by which obesity affects male fertility remain unclear.

Lifestyle can influence male spermatogenesis and fertility [12]. Western diet has been regarded as a risk factor for male infertility due to the increased oxidative stress and lower testosterone levels via saturated fatty acids intake [13]. Another study has demonstrated that dietary polyunsaturated fatty acids can be useful in male infertility [14]. Animal experiments show that High-Fat Diets (HFD) during early life correlates with testicular ectopic lipid deposition and low sperm quality [15], and HFD even damage sperm counts decrease in grandsons [16] via Transgenerational effects [17]. In addition, existing research has recognized that more moderate exercise improves spermatogenesis and semen quality by increasing body antioxidant defence and reducing pro-inflammatory cytokines level [18]. These results support a rationale for the under-standing of the hormonal and inflammation axis. Recent studies on obesity-mediated male infertility [19] have focused on alterations in the Hypothalamus–Pituitary–Gonad (HPG) axis, disruption of testicular steroidogenesis, metabolic abnormalities (disruption of insulin, cytokine, and adipokine homeostasis), and epigenetic aspects. In different studies, the prevalence of hypogonadism in obese men have been determined to be high, ranging from 40% to 79%. The complex interactions among excess body weight, body composition, sex steroids, and hypogonadism have been widely recognized [20]. Testosterone is a steroid hormone secreted by the testes in men. The hormone is important for the maintenance of male secondary sexual characteristics [21]. In men, a low androgenic status reduces total testosterone level, which is a frequent feature of visceral obesity [22]. Obese individuals display increased estrogen concentrations due to the overexpression of aromatase in adipose tissue. Such men present with symptoms of hypogonadotropic hypogonadism [23]. The use of Aromatase Inhibitors (AIs) can restore the balance between testosterone and estradiol levels and optimize the HPG axis to support spermatogenesis. AIs, including letrozole and anastrozole, have been used to treat male infertility for decades [24]. Excessive accumulation of adipose tissue around male gonads may lead to insufficient local androgen concentration, in turn leading to dysfunctional testicular development and penile dysplasia.

In this study, we predicted the causal relationship between obesity and male infertility using a Mendelian Randomization (MR) analysis based on data from large Genome-Wide Association Study (GWAS) datasets and bioinformatic analyses to predict the pathways that may play a role. A mouse model of obesity was developed to validate the role of aromatases in the process of obesity-mediated male fertility impairment.

Materials and Methods

GWAS Summary Data of Obesity and Male Infertility

All GWAS summary data can be found in the GWAS catalog (https://www.ebi.ac.uk/gwas/). The GWAS catalog provides a consistent, searchable, visualizable, and freely available database of Single Nucleotide Polymorphism (SNP)-trait associations, which can be easily integrated with other resources [25]. We used published GWAS summary data for childhood obesity [26]. The analyzed data included 5,530 obesity cases (=95th percentile of BMI achieved before 18 years of age, representing 5-30% of any given cohort) and 8,318 controls (relatively conservatively defined as <50th percentile of BMI consistent throughout all measures during childhood) of European ancestry, with data from 14 discovery cohorts including the Avon Longitudinal Study of Parents and Children (ALSPAC), Northern Finland 1966 Birth Cohort (NFBC1966), British 1958 Birth Cohort - Type 1 Diabetes Genetics Consortium subset (B58C-T1DGC), British 1958 Birth Cohort - Wellcome Trust Case Control Consortium Subset (B58C-WTCCC), French Young study (FRENCH YOUNG), Lifestyle Immune System Allergy Study (LISA), Western Australian Pregnancy Cohort study (RAINE), Children’s Hospital of Philadelphia (CHOP), Essen Obesity Study (ESSEN), Helsinki Birth Cohort Study (HBCS), Cardiovascular Risk in Young Finns Study (YF), Copenhagen Study on Asthma in Childhood (COPSAC), CM-GOYA study (CM-GOYA), and Generation R Study (GENERATIONR).

GWAS summary data for three clinical classes of obesity have been published [27]. The analyzed data for obesity class1 included 32,858 obesity cases (BMI =30 kg/m²) and 65,839 controls (BMI <25 kg/m²). The obesity class 2 data included 9,889 obesity cases (BMI =35 kg/m²) and 62,657 controls. The analyzed data for obesity class 3 included 2,896 obese patients (BMI =40 kg/m2) and 47,468 controls.


MR using summary data from GWAS is an increasingly important tool for appraising causality in hypothesized exposure-outcome pathways. For each direction of potential influence, we combined MR estimates using inverse variance weighted (IVW) meta-analysis. This analysis essentially translates to a weighted regression of SNP-outcome effects on SNP-exposure effects, where the intercept is constrained to zero [28]. MR analyses were performed using MR-Base (default settings) (http://app.MrBase.html.org/). In addition to simple lookup requests for individual SNPs across multiple GWAS, MR-Base automates the implementation of two-sample MR, including effect allele harmonization across separate studies, linkage disequilibrium pruning to ensure independence of genetic variants, and diagnostic and sensitivity analyses [29]. Statistical significance was set at P<0.05.

Expression Omnibus (GEO) Database

Gene profiles (GSE6872, GSE55200) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). GSE6872 datasets [30] prepared from the semen samples of 21 individuals. They included semen samples from 13 normally fertile males who had fathered at least one child and from eight infertile individuals with severe and consistent heterogeneous teratozoospermia who showed no other abnormal semen parameters. Subcutaneous adipose tissue samples of GSE55200 datasets were obtained from the periumbilical region under local anesthesia and after an overnight fast. Previously described microarrays [31] were used to examine differences in subcutaneous adipose tissue gene expression in seven lean healthy controls and 16 obese individuals.

Gene Function Analysis

All datasets were downloaded from the GEO database through the “GEOquery” (v. 2.54.1) package [32]. The probes corresponding to multiple molecules were removed. If probes corresponding to the same molecule were encountered, only the probe with the highest signal value was retained. Statistical analysis and visualization were performed using the R package modules “limma” (v. 3.42.2) [33], “umap” (v., “ComplexHeatmap” (v. 2.2.0) [34], and “ggplot2” (v. 3.3.3). Differentially Expressed Genes (DEGs) were identified with |log2FC|>1 and an adjusted P-value<0.05. Gene Ontology (GO) enrichment analysis [35] was performed to enrich DEGs according to Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). Enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.genome.jp/kegg/) [36] was performed to identify and confirm the related signaling pathways of DEGs. GO and KEGG enrichment analyses were performed using the R package modules of “org.Hs.eg.db” (v. 3.11.4) and clusterProfiler” (v. 3.17.3). Gene Set Enrichment Analysis (GSEA) [37] was used to focus on group of genes that share common biological function, chromosomal location, or regulation. GSEA was performed using GSEA (v. 3.0). The Broad Molecular Signatures Database (MSigDB v. 7.4, https://www.gsea-msigdb.org/gsea/msigdb/) C2: curated gene sets (KEGG pathway) summarize and represent specific well-defined biological states or processes.

Animals and Diets

C57BL/6J mice were purchased from Xi’an Jiao Tong University Animal Experiment Center (ID: SCXK 2021-153). The mice were housed using alternating 12-h light/dark cycles with ad libitum access to food and water. Male mice were randomly assigned to a HFD (60% fat, Supplementary Information 1, n=8) to induce obesity or a normal chow diet (n=8). Body weights were recorded per two weeks. All animal experiments took place at Scientific Research and Experiment Center of Xi’an Jiaotong University Second Affiliated Hospital. This study was approved by the Ethics Committee of Xi’an Jiaotong University Second Affiliated Hospital. We confirm that all methods were performed in accordance with the relevant guidelines and regulations.

Serological Indicators Detection of Mice

C57BL/6J mice were starved overnight one day before sacrifice at 18 weeks of age. All mice were anaesthetized by intraperitoneal injection with 0.3% pentobarbital sodium injection (50mg/kg, NDC 67386-501-55). At the completion of the study, mice were euthanized with pentobarbital sodium (100 mg/kg). Blood samples were obtained for further biochemical analyses and were centrifuged at 3000g for 10 min at 4°C after standing for 2h in room temperature; serum was isolated and stored at -80°C. The levels of Free Fatty Acids (FFA), insulin, FSH and testosterone in serum were detected by Enzyme-Linked Immunosorbent Assay (ELISA). ELISA requires several experimental steps, including antibody immobilization, target binding, labeling, substrate incubation, signal production, and multiple washing steps.

Tissue Collection and Histological Analyses

Before tissue collection, the anesthetic (0.3% pentobarbital sodium) was continued until the mice were euthanized. Epididymal white adipose tissue (eWAT), liver, and testis tissues of mice were harvested for histological analyses and RNA extraction. The eWAT tissue was fixed in formalin for 24 h, followed by washing in 70% ethanol. Paraffin-embedded sections (5 μm) were cut, dewaxed, and stained with hematoxylin and eosin. Images were scanned using an Aperio ImageScope and analyzed using ImageScope software (Leica). To determine testicular lipid accumulation, frozen sections of the testes (10 μm) were fixed in 95% ethanol for 10s, washed with distilled water for 10s, stained with Oil Red O for 10 min, washed again with distilled water for 10s, and counterstained with hematoxylin for 30s. To evaluate the consequences of the previously described delay in spermatogenic development at the level of sperm chromatin condensation and DNA damage, we performed the terminal deoxynucleotidyl Transferase dUTP Nick End Labelling (TUNEL) to examine DNA damage.

Gene Expression

Total RNA was extracted from the tissues. cDNA was synthesized using a high-capacity cDNA synthesis kit (Takara). Targeted RT-qPCR assays were run in 20-μL triplicate reactions using iTaq SYBR Green Supermix (Takara). Gene expression levels were calculated after normalization to the housekeeping gene Β-tubulin using the 2–ΔΔCt method. The expression levels were expressed as relative mRNA levels compared to the control. The primers used are listed in Table 1.