Shift from visceral to subcutaneous adipose tissue in Cyp17a1-knockout rats prevents the progression of metabolic syndrome

Beom-Jin Jeon; Jeong-Hwa Lee; Dong-Hyeok Kwon; Hee-Kyoung Kim; Goo Jang

doi:10.1371/journal.pone.0311478

Abstract

In this study, we investigated the effects of Cyp17a1 gene knockout (KO) on obesity and metabolic syndrome. Cyp17a1 KO in rats using CRISPR-Cas9 resulted in sex dimorphism and obesity, and interestingly, site-specific accumulation was found in subcutaneous adipose tissue (SAT). Surprisingly, an insulin tolerance test and oral glucose tolerance test did not show any issues with insulin sensitivity and secretion despite hyperglycemia. In addition, Cyp17a1 KO rats showed normal plasma insulin and free fatty acid levels compared to wild-type rats, and blood biochemistry analysis revealed normal triglyceride, total cholesterol, high-density lipoprotein, and low-density lipoprotein levels. Cyp17a1 KO adipose-tissue-derived stem cells from SAT showed increased expression of KLF5, an early adipogenesis marker, which implies enhanced adipogenic potential in SAT. When gene expression associated with lipid, glucose, and insulin metabolism as well as inflammation in adipose tissue was examined, a metabolic shift to SAT was discovered in the Cyp17a1 KO group. In conclusion, in the Cyp17a1 KO rat models we generated for the first time, the phenotype promoted by obesity reflected metabolically healthy obesity hypothesis, but this did not exhibit metabolic syndrome-like features due to enhanced metabolism in the SAT.

Citation: Jeon B-J, Lee J-H, Kwon D-H, Kim H-K, Jang G (2025) Shift from visceral to subcutaneous adipose tissue in Cyp17a1-knockout rats prevents the progression of metabolic syndrome. PLoS One 20(12): e0311478. https://doi.org/10.1371/journal.pone.0311478

Editor: Akingbolabo Daniel Ogunlakin, Bowen University, NIGERIA

Received: September 19, 2024; Accepted: November 5, 2025; Published: December 12, 2025

Copyright: © 2025 Jeon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This study was financially supported by the National Research Foundation of Korea (NRF-2021R1A5A1033157) for the SRC program: Comparative Medicine Disease Research Center (Project 382), the Research Institute of Veterinary Science, the BK21 Four Future Veterinary Medicine Leading Education and Research Center, and the Ministry of Food and Drug Safety (MFDS) of Korea (20182MFD501). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Obesity has become a global health concern, leading to an increase in diabetes, high blood pressure, and cardiovascular disease, among other disorders [1]. Metabolic syndrome is the term for the complex physical condition that includes diabetes and cardiovascular illnesses brought on by obesity [2–4]. As the prevalence of obesity increases, there is a corresponding rise in the incidence of metabolic syndrome [5]. This trend underscores the urgency of advancing research into the mechanistic pathways that link obesity to subsequent metabolic disorders such as diabetes and cardiovascular diseases [6,7]. In this respect, adipose tissue is one of the main focuses of research regarding the progression of metabolic syndrome [8,9].

Adipose tissue is now understood to engage in cross-talk with other organs as well as within itself, functioning as a type of endocrine gland that regulates blood glucose and free fatty acid concentrations through lipolysis and lipogenesis [10]. Additionally, adipose tissue secretes adipokines such as leptin and adiponectin, which are known to regulate not only energy storage but also obesity and insulin resistance [11–14]. Recent studies on the role of adipose tissue in metabolic syndrome development have focused on the different roles of visceral adipose tissue (VAT) and SAT. VAT is located inside the abdominal cavity and dysfunction in VAT can lead to metabolic diseases due to inflammation and disturbed metabolic balance [15–17]. In contrast, SAT appears to have a protective role, as its release of adipokines can prevent the progression of metabolic syndrome and prevent excess fat storage in VAT and ectopic depots including the liver [16–20]. Considering these distinct roles of different adipose tissues, targeted research on each specific type of fat is crucial for a comprehensive understanding of metabolic syndrome and obesity [19,21]. Furthermore, considering that obesity is a major risk factor for numerous metabolic derangements and related diseases which can be caused by monogenic or polygenic factors [22], there is a compelling need to delve into the genetic architecture of obesity to better understand and potentially mitigate its impact [23].

The Cyp17a1 gene is involved in steroidogenesis and is required for the synthesis of glucocorticoids and sex hormones [24]. The Cyp17a1 gene has recently been linked to both sex dimorphism and atherosclerosis [25–28]. Furthermore, some research findings indicate that obesity develops from a mutation in the Cyp17a1 gene [29,30]; however, the exact mechanism underlying obesity and the impact of obesity on metabolic syndrome resulting from Cyp17a1 gene mutation remains unknown. Furthermore, not enough is known about the impact of Cyp17a1 gene knockout (KO)-induced modifications in steroidogenesis and its effects on adipokine production and lipid metabolism in adipose tissue depot specifically.

Therefore, the goal of this research was to find out how the Cyp17a1 gene alters adipose tissue metabolism and how this influences the development of obesity and the resulting metabolic syndrome. To achieve this, we produced Cyp17a1 KO rats and verified their obesity phenotype, assessing key components of metabolic syndrome including blood glucose levels, blood pressure, glucose tolerance, and insulin resistance. We also separately isolated subcutaneous and visceral (perigonadal) adipose tissue to examine alterations in the metabolism of adipose tissue and adipose-derived stem cells (ADSCs).

Materials and methods

Animals

All animal care and procedures were approved by the Institutional Animal Care and Use Committee (No.201222-4-2) of Seoul National University Institute of Laboratory Animal Resources and performed under the guidelines of Seoul National University. SD rats used in this study were purchased from Orient-Bio (Seoungnam, Republic of Korea) and maintained at 24 ± 2°C, 50% humidity, and a 12:12 h light-dark cycle (lights on from 07:00–19:00).

Superovulation and embryo collection

Female rats were induced to superovulate by an intraperitoneal injection of 150 IU/kg Pregnant mare serum gonadotrophin (Daesung Microbiological Labs, Republic of Korea) and 150 IU/kg human chorionic gonadotrophin (Daesung Microbiological labs) with a 48-h period, and then mated with males. Rats were anesthetized with an intramuscular injection of a 1.5 mg xylazine (Rompun®, Elanco Korea, Republic of Korea) and 0.35 mg alfaxalone (Alfaxan® multidose, Jurox, Australia) mixture and euthanized by cervical dislocation. One-cell-stage embryos were collected in M2 medium (Sigma-Aldrich, USA) from oviducts of females the day after mating, and cultured in mR1ECM medium (Cosmobio, Japan).

gRNA synthesis, embryo electroporation and embryo transfer

Guide RNA (gRNA) for Cyp17a1 knockout was designed using an online tool (CRISPR RGEN tool; http://www.rgenome.net/) and synthesized using a precision gRNA synthesis kit (Invitrogen, USA). The gRNA sequences used in this study are described in S1a Fig. A total of 200 ng/μL gRNA and Cas9 RNP (1:1) were incubated for 5 min and transfected into one-cell stage rat embryos using Genome Editor (GEB15, BEX, Japan) in conditions of 30 V, 7 times for 3 msec, and 97 msec intervals. Two-cell stage embryos were transferred to the oviducts of pseudo-pregnant recipient females.

Embryo cryopreservation

Embryo cryopreservation was conducted as previously described [31]. Briefly, two-cell stage rat embryos were washed 3 times using M2 medium and BoviFreeze (Minitube, Germany) subsequently. Washed embryos were loaded in a Ministraw (Minitube) and frozen using Freeze Control embryo freezers (CL8800i, Minitube).

Genotyping

Genomic DNA for genotyping was extracted from the rat tails using a DNeasy Blood & Tissue Kit (Qiagen, Germany). PCR for Cyp17a1 amplification was conducted using Mastercycler X50a (Eppendorf, Germany). Primers used in PCR are listed in S1 Table. Animals were genotyped and categorized as wild-type (+/+), heterozygous (+/−), or homozygous knockout (−/−).

qPCR analysis

Total RNAs were extracted from rat gonad tissues and adipose tissues using an RNeasy Mini Kit (Qiagen) and 5 µg of total RNA was used for synthesizing complementary DNA (cDNA) using an RNA to cDNA EcoDry™ Premix Kit (Clontech, USA). Quantitative PCR (qPCR) was conducted in a MicroAmp™ Optical 96-Well Reaction Plate (Applied Biosystems, USA) using TB Green^® Premix Ex Taq™ (TAKARA, Japan). Quantitative PCR was conducted using a Quantstudio 1 Real-Time PCR instrument (Applied Biosystems). Target-gene-related expression was normalized to Actb expression using the comparative CT (2^-ΔΔCt) method. Primers used in qPCR are listed in S1 Table.

Estradiol and testosterone assay

Serum estradiol and testosterone were assessed with an electrochemiluminescence immunoassay (ECLIA) Elecsys Estradiol III and Testosterone II (Roche, Switzerland) conducted by the Global Clinical Central Lab (GCCL, Republic of Korea) using a Cobas 8000 e801 (Roche). For assessment of estradiol, two biotinylated monoclonal anti-estradiol antibodies (rabbit) were used at concentrations of 2.5 ng/ml and 4.5 ng/ml, the measuring range (defined by the limit of detection and the maximum of the master curve) was 5–3000 pg/mL and the intra-assay coefficient of variation was < 8.6% relative SD. For assessment of testosterone, biotinylated monoclonal anti-testosterone antibodies (rabbit) were used at a concentration of 40 ng/mL, the measuring range (defined by the limit of detection and the maximum of the master curve) was 0.025–15 ng/mL, and the intra-assay coefficient of variation was < 5.7% relative SD. A radioimmunoassay was used to determine the concentrations of estradiol and testosterone.

Adipocyte size analysis

The adipocyte size in the adipose tissue was measured according to previous studies [32]. Briefly, adipocyte boundary segmentation was primarily conducted using AdipoCount software [33] and then was re-segmented manually to improve accuracy. Segmented adipocyte images were analyzed using ImageJ software [34]. Image thresholds were adjusted from 55 to 255, and adipocyte sizes were analyzed with the “Analyze Particles” menu, with size = 500−30,000 µm². All analyzed adipocyte size data were distributed into 1000 µm² units.

Insulin tolerance test and oral glucose tolerance test

For the insulin tolerance test (ITT), rats were fasted overnight and weighed. Blood sugar was measured using a glucometer before and 15, 30, 45, 60, 90 and 120 min after intraperitoneal insulin injection (0.5 IU/kg bodyweight; Humulin R, Eli Lilly and Company, USA). The time required for blood sugar levels to decline by 50% (t_1/2) was calculated by linear regression and the K_ITT value was calculated by the following equation:. For the oral glucose tolerance test (OGTT), rats were fasted overnight and weighed. Blood sugar was measured using a glucometer before and 30, 60, 90, and 120 min after intragastric glucose administration (2 g/kg body weight; 50% Dextrose Inj, Dai Han Pharm Co., Republic of Korea).

Blood pressure measurement

Indirect measurement of systolic blood pressure (SBP) was carried out using the tail-cuff method (ML125; Powerlab, AD Instruments, Castle Hill, NSW, Australia). Before SBP measurement, the rats (24-week-old normal diet-fed rats and 15-week-old high-fat diet-fed rats) were placed in a warming chamber set at approximately 34°C for 15 minutes, followed by placement in a plastic restrainer. To minimize stress-induced pressure changes, the animals were acclimated to the measurement conditions of the plethysmograph beforehand. SBP measurements were consistently taken between 10 AM and 12 PM. A minimum of five consecutive measurements were recorded using the data acquisition system (LabChart® software, version 7.1; ADInstruments, Colorado Springs, CO) to determine the mean SBP for each rat.

Plasma insulin and free fatty acid analysis

Blood was collected in EDTA tubes from rats fasted overnight, and plasma was separated using a centrifuge at 1500 x g for 10 min. Fasting insulin was assessed using a Rat Insulin ELISA Kit (RTEB0287, AssayGenie, Ireland) following the manufacturer’s instructions and measured using a SpectraMax ABS microplate reader (Molecular Devices, USA). The fasting free fatty acid level was assessed using a Free Fatty Acid Assay Kit (ab65341, Abcam, United Kingdom) following the manufacturer’s instructions and measured using a SpectraMax ABS microplate reader.

ADSC isolation and adipogenic differentiation

Perigonadal and inguinal adipose tissues were dissected from 14-to-15-week-old rats and minced using surgical blades. Minced tissues were digested in 10 mL of 0.05% collagenase type I (Gibco, USA)/HBSS (Gibco) for 30 min at 37°C in a 5% CO₂ incubator. Digested tissues were centrifuged at 2000 x g for 5 min, and the supernatant was discarded. Centrifuged stromal vascular fractions were filtered through 70 µm nylon mesh and transferred to new 1.5 mL tubes and red blood cells were lysed using eBioscience™ 1X RBC Lysis Buffer (Invitrogen). ADSCs were cultured in 20% fetal bovine serum (Gibco)/DMEM (Cytiva, USA) supplemented with 1% Pen/Strep (Gibco). ADSCs were grown to 90% confluence and differentiated into adipocytes using a StemPro™ Adipogenesis Differentiation Kit (Gibco) following the manufacturer’s instructions.

Neutral lipid-positive pixel counts

Differentiated adipocytes were stained using BODIPY™ 493/503 (Invitrogen) and 9 images per each group were collected using an EVOS M7000 (Invitrogen) at the same locations. The color channels of the images were split, and green channel images were used for analysis. The threshold for measuring the ratio of green fluorescence positive pixels was set between 55 and 255, and only pixels within this range were counted.

Statistical analysis

Data were analyzed using Student’s t-test, which was performed using GraphPad Prism version 8.0.1 for Windows (GraphPad Software, USA, www.graphpad.com). When the p-value was lower than 0.05, the results were considered statistically significant. The exact meaning of the symbol is included in the figure legends.

Results

CYP17A1-deficient rats showed disorders of sex development and obesity with increased subcutaneous adipose tissue

Using the CRISPR-Cas9 system, the sequence following the Cyp17a1 gene start codon was targeted and Cyp17a1 KO rats were produced (S1a Fig). PCR analysis and Sanger sequencing at the genomic DNA level were used to primarily validate the gene’s knockout and a 295-bp deletion at the target region was discovered (S1b–e Figs). Males with CYP17A1 deficiency had a sex-reversed phenotype at their external genitalia due to CYP17A1’s involvement in steroidogenesis (Figs 1a–1d). In addition, the reproductive tracts of Cyp17a1 KO rats displayed disorders of sex development, including underdeveloped uteri and failed folliculogenesis in females and defective spermatogenesis in males (Figs 1e–1h). H&E staining further revealed thinner uteri in KO females compared with wild-type female rats (224.4 µm vs. 903.5 µm; Figs 1i, 1j) accompanied by absence of mature follicles and corpus luteum (Figs 1k, 1l). Similarly, testes of Cyp17a1 KO males lacked normal spermatogenesis (Figs 1m, 1n). Quantitative PCR analysis confirmed reduced Cyp17a1 mRNA expression in the Cyp17a1 (+/−) group and complete loss in knockout group (Fig 1o). To assess the impact of Cyp17a1 gene knockout on sex hormone production, ECLIA was used to evaluate the levels of testosterone and estradiol in the serum of wild-type and Cyp17a1 KO rats. Cyp17a1 KO males and females were confirmed to have impaired testosterone and estradiol production, respectively (Figs 1p, 1g). As these Cyp17a1 KO rats are sterile, we maintained the line by mating Cyp17a1 (+/−) males and females and cryopreserved the embryos.

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Fig 1. Phenotype of Cyp17a1 knockout rats.

a-d) External genitalia of rats. Red arrows indicate distance between anus and genitals. e-h) Reproductive tracts of rats. i-j) Representative images of H&E-stained uterus of female rats. Thickness of the uterus is indicated in the images. k-l) Representative images of H&E-stained ovary of female rats. SF: secondary follicle, AF: Antral follicle, CL: corpus luteum. m-n) Representative images of H&E-stained testis of male rats. Scale bars = 100µm. o) Cyp17a1 mRNA qPCR results of rats. Gonads from each group were used for qPCR analysis (n = 3). The data were normalized to Actb and are presented as means±SEM. * p < 0.05, **** p < 0.0001, using Student’s t-test. p-q) LC-ECLIA result of serum estradiol and testosterone concentration in wild-type and Cyp17a1 knockout rats (n = 3).

https://doi.org/10.1371/journal.pone.0311478.g001

We also monitored the body weight of CYP17A1-deficient rats fed a high-fat diet since prior research had shown that mice with this gene defect have an obesity-related phenotype [30]. Cyp17a1 KO females had greater body weights than wild-type females (Figs 2a, 2c-2d', 2g) despite having equal muscle weights (Figs 2b). Interestingly, an increase in VAT and SAT was observed in the KO female group (Figs 2h, 2i) and an increased fat-to-body-weight ratio was also confirmed (Figs 2j, 2k). This trend was also observed in the male group, where, despite their body weight being comparable to that of the wild-type males (Figs 2a, 2e-2f’, 2g), a similar or slightly greater amount of fat was accumulated in KO males (Figs 2h, 2i). Interestingly, the ratio of SAT to body weight rose dramatically in both the Cyp17a1 KO male and female groups (Figs 2j, 2k). Furthermore, it was discovered that the ratio of SAT to VAT was also considerably increased in both the Cyp17a1 KO male and female groups (Fig 2l). In the group following a chow diet, this trend remained the same. Although body weight was not significantly different from that of wild-type females and was less than that of wild-type males (S2a,b Figs), there was a statistically significant increase in the amount of fat that each KO group had acquired, particularly in SAT (S2c–l Figs). In both the KO male and female, hypertrophy of VAT and SAT was observed by adipocyte size measurement using H&E staining (Figs 2m–2p, S3a–d Figs). Remarkably, these outcomes were shown to a similar extent in both the male and female groups that were given a chow diet (S3e–l Figs).

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Fig 2. Fat distribution of Cyp17a1 knockout HFD fed rats.

a) Body weight measurement of HFD fed rats. Cyp17a1 knockout rats (n = 8, male; n = 12, female) and wild-type rats (n = 4) were measured. ***p < 0.001, ****p < 0.0001, using Student t-test. b) Mass of skeletal muscle (tibialis anterior) of rats. (n = 3, wild-type female; n = 4, the other group) c-f’) Representative images of subcutaneous adipose tissue of HFD fed rats. Red circles indicate inguinal adipose tissue. g-l) Sampling results of rats. (g) Body weight, (h) mass of visceral adipose tissue, (i) subcutaneous adipose tissue, (j, k) relative mass of visceral and subcutaneous adipose tissue normalized to body weight. (l) Relative subcutaneous adipose tissue mass normalized to visceral adipose tissue. m-n’) Representative images of H&E-stained adipose tissue of HFD fed female rats. Visceral adipose tissue of Cyp17a1 knockout female rat (m), wild-type female rat (m’). Subcutaneous adipose tissue of Cyp17a1 knockout female rat (n) and wild-type female rat (n’). Scale bar = 100µm. o, p) Adipocyte size analysis of perigonadal adipose tissue (o) and subcutaneous adipose tissue (p). Images of H&E-stained adipose tissue were analyzed using ImageJ program (https://imagej.net/ij/). # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001, lower than wild-type. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, higher than wild-type, using Student’s t-test, (n = 12).

https://doi.org/10.1371/journal.pone.0311478.g002

CYP17A1 deficiency in rats did not induce metabolic syndrome despite their obesity and hyperglycemia

As in previous results, Cyp17a1 homozygous knockout (-/-) rats showed signs of obesity, including a particular rise in SAT and adipose tissue hypertrophy. Because CYP17A1 is involved in steroidogenesis and earlier studies have shown that changes in sex hormones are associated with insulin resistance [35–38], we conducted a series of assays to investigate the effect of its deficiency on metabolic syndrome. First, to examine if sexual maturation differs in metabolic syndrome between Cyp17a1 KO rats and wild-type rats, we conducted an insulin tolerance test on chow-diet-fed rats at 5, 12, and 20 weeks old. At all three stages of age and in both sexes, there was no discernible difference in the KO group’s and wild-type group’s responsiveness to insulin (S4a–i Figs). When an insulin tolerance test was conducted on the high-fat-diet-fed group, males and females in the Cyp17a1 KO rats had significantly higher blood sugar levels than the wild-type group (Figs 3a, 2a’, 2d). However, the degree of drop in plasma glucose level after insulin injection was comparable to that in wild-type rats (Figs 3b, 3b’) and the K_ITT value, which indicates the percentage decline in plasma glucose concentration per minute, was also similar to that of wild-type (Figs 3c, 3c’).

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Fig 3. Metabolic analysis in Cyp17a1 KO HFD fed female rats.

a-c’) Results of insulin tolerance test (ITT) of HFD fed rats (n = 12, Cyp17a1 knockout group; n = 4, wild-type group). a, a’) Blood glucose level after insulin injection and b, b’) percentage of blood glucose to fasting glucose level. ## p < 0.01, lower than wild-type, *p < 0.05, **p < 0.01, ***p < 0.001, higher than wild-type rats, using Student’s t-test. c, c’) K_ITT value which indicates percentage decline in blood glucose concentration per minute. d) Overnight-fast glucose level of HFD fed rats (n = 12, Cyp17a1 knockout group; n = 4, wild-type group). e, e’) Results of oral glucose tolerance test (OGTT) of HFD fed rats. *p < 0.05 **p < 0.01, higher than wild-type, using Student’s t-test (n = 12, Cyp17a1 knockout group; n = 4, wild-type group). f) Plasma insulin level of HFD fed rats analyzed with ELISA. g) Plasma insulin changes of HFD fed rats to chow diet-fed rats (n = 6, Cyp17a1 knockout group; n = 3 wild-type group). h) Blood pressure of HFD fed rats. i) Plasma free fatty acid level of and j) free fatty acid level changes of HFD fed rats to chow diet-fed rats (n = 6, Cyp17a1 knockout group; n = 3 wild-type group).

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Subsequently, a glucose tolerance test was conducted on the rats to assess the insulin secretion response to glucose administration. In glucose tolerance tests conducted on Cyp17a1 KO rats and wild-type rats fed a standard diet, no significant differences were observed between males and females in either group (S4j,k Figs). Furthermore, males lacking the Cyp17a1 gene displayed a reduced rise in blood glucose. However, when glucose tolerance tests were performed on rats fed a high-fat diet, significant differences were found between the KO female and wild-type female (Fig 3e). No such distinct differences were observed in the male Cyp17a1 KO group, indicating a gender-specific response (Fig 3e’). When the plasma insulin concentration was measured, it was discovered that the insulin levels of the Cyp17a1 KO females were similar to those of the wild-type females when they followed the chow diet and the high fat diet, while the insulin levels of the males did not increase when they followed the high fat diet, in contrast to the wild-type males (S4l Fig, Figs 3f, 3g). Together with the earlier OGTT results, these data suggest that the reason Cyp17a1 KO female’s blood sugar levels were higher was not due to an issue with insulin secretion, but rather due to hyperglycemia, which caused the blood sugar to be elevated overall.

To examine the metabolic syndrome caused by CYP17A1 deficiency in more detail, a blood biochemistry test was conducted. Although KO females fed the chow diet showed higher triglyceride levels, they did not exceed the normal reference range (14.2–78.8 mg/dL, [39]) and the triglyceride, total cholesterol, HDL and LDL levels in the other groups were identical or even lower than those of wild-type females under both the high-fat diet and chow diet (Table 1, S2 Table). Both their free fatty acid level in plasma and blood pressure were the same in every group (Figs 3h–3j, S4m Fig). Considering previous research showed that elevated levels of free fatty acids lead to insulin resistance [10,38], these findings provide more context for the observed hyperglycemia in KO rats but equivalent insulin responses to wild-type rats. Furthermore, Cyp17a1 KO rats did not exhibit the rise in plasma insulin concentration that is frequently seen in patients with metabolic syndrome, even when they were given a high-fat diet. Despite causing obesity-induced hyperglycemia, the Cyp17a1 gene knockout did not affect insulin secretion or responsiveness. This shows that CYP17A1 deficiency cannot be considered to lead to a metabolic syndrome.

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Table 1. Blood biochemistry of Cyp17a1 knockout and wild-type rats with high fat diet.

https://doi.org/10.1371/journal.pone.0311478.t001

Enhanced adipogenesis in ADSCs from Cyp17a1 knockout rats

ADSCs were cultured from fat samples to investigate the etiology of obesity in the Cyp17a1 KO group. Subsequently, adipogenic differentiation was induced and variations in adipocyte production were examined using neutral lipid staining. Based on the results of previous experiments which demonstrated more pronounced obesity and more prominent fat accumulation in the female group, ADSCs were isolated from VAT and SAT in the high-fat-diet-fed female group and used in the following experiment about adipogenic potentials. Up until day 4, there was no discernible difference between the Cyp17a1 KO ADSCs and the wild-type ADSCs isolated from VAT; however, on day 6, considerable differentiation was seen (Figs 4a,4a’,4c,4c’,4e). On the other hand, ADSCs isolated from SAT in the Cyp17a1 KO group consistently showed higher levels of neutral lipid formation, even before adipogenic stimulation (Figs 4b,4b’,4d,4d’,4f). To examine the adipogenic differentiation of ADSCs in further detail, RNA was isolated from differentiated ADSCs and qPCR was performed. During the 6-day period of induced adipogenic differentiation, explosive increases in the expression of early adipogenesis marker KLF5 and late adipogenesis markers PPARγ and C/EBPα were observed in both perigonadal and SAT from KO rats (Figs 4g–4i’). Interestingly, while KLF5 expression was reduced in VAT-derived ADSCs from Cyp17a1 KO rats, it was enhanced in subcutaneous-fat-derived ADSCs from Cyp17a1 KO rats.

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Fig 4. Adipogenesis using adipose-derived stem cell (ADSC) from Cyp17a1 KO rats.

a-d’) Representative images of adipogenesis using ADSCs from rats on day 6. Bright and fluorescent images of Cyp17a1 KO ADSCs from perigonadal adipose tissue (a, a’) and subcutaneous adipose tissue (b, b’), and wild-type ADSC from perigonadal adipose tissue (c, c’) and subcutaneous adipose tissue (d, d’). Scale bar = 250µm. e, f) Results of neutral lipid positive pixel count using ImageJ program. Result of perigonadal adipose tissue derived stem cell (e) and subcutaneous adipose tissue derived stem cell (f). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 using Student’s t-test (n = 9). g-i’) qPCR results of mRNAs from differentiated ADSCs on day 0, 2, 4, 6. Relative Klf5, Pparg, Cebpa mRNA expression level from differentiated ADSCs from perigonadal adipose tissue (g-i) and subcutaneous adipose tissue (g’-i’). The data were normalized to Actb and are presented as means±SEM. #### p < 0.0001, lower than wild-type, **p < 0.01, ***p < 0.001, ****p < 0.0001, higher than wild-type, using Student’s t-test (n = 6).

https://doi.org/10.1371/journal.pone.0311478.g004

Metabolic shift from visceral to subcutaneous adipose tissue due to Cyp17a1 gene knockout

RNA was then isolated from the previously sampled female adipose tissues and qPCR was conducted to confirm fat-related metabolism and inflammation. Remarkably, there was a confirmed decrease in the expression of several genes linked to fat metabolism in VAT and a rise in SAT (Fig 5). When comparing the two lipogenesis-related genes Srebf1 (SREBP-1c; sterol regulatory element-binding protein 1c) and Dgat (DGAT; diglyceride acyltransferase), the Cyp17a1 KO group exhibited an overall higher gene expression level in SAT but lower or no significant difference in VAT compared to wild-type group (Figs 5a, 5b). The CYP17A1 deficiency also upregulated the three lipolysis-related genes, Lipe (HSL; hormone-sensitive lipase), Prkaca (PRKACA; protein kinase cAMP-activated catalytic subunit alpha), and Pnpla2 (ATGL; adipose triglyceride lipase) in SAT and lower or no significant differences in VAT (Figs 5c–5e). In both VAT and SAT, the expression levels of Abhd5 (ABHD5; abhydrolase domain containing 5) and G0s2 (G0S2; G0/G1 switch 2), a co-activator and regulator of ATGL respectively, were lower or did not differ significantly (Figs 5f, 5g), which means altered lipolysis activity in both adipose tissues is not regulated by the activity of other genes. The expression of three genes, Mlxipl (ChREBP; carbohydrate-responsive element-binding protein), Slc2a4 (GLUT4; glucose transporter 4), and Acaca (ACACA; acetyl-CoA carboxylase alpha), related to glucose signaling lipogenesis, and two genes, Irs1 (IRS1; insulin receptor substrate 1) and Pik3ca (PIK3CA; phosphatidylinositol-4,5-biphosphate 3-kinase, catalytic subunit alpha), related to the insulin signaling pathway, were examined to confirm whether this shift in fat metabolism to SAT is related to glucose and insulin signaling. The results showed that VAT in Cyp17a1 KO rats had decreased expression of genes related to glucose-induced lipogenesis, while SAT showed an upregulation in this pathway (Figs 5h–5j). Insulin signaling was found to be reduced in VAT of Cyp17a1 KO rats and to be statistically comparable to that of wild-type rats in SAT (Figs 5k, 5l), indicating reduced insulin-mediated lipogenesis in VAT and a normal insulin signaling pathway in SAT. Subsequently, the expression levels of inflammation-associated genes Tnf (TNFα; tumor necrosis factor-alpha) and Il6 (IL6, interleukin 6) were compared to examine inflammation in adipose tissue. In the SAT of Cyp17a1 KO rats, the expression of these genes was either the same or lower than in the wild-type rats, while in the VAT, Il6 was more highly expressed and Tnf had lower expression levels (Figs 5m, 5n). Lastly, expression of the insulin resistance-related Agt (AGT; angiotensinogen) and Adipoq (AdipoQ; adiponectin) genes was found to be higher in SAT and lower in VAT in Cyp17a1 KO rats (Figs 5o, 5p).

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Fig 5. qPCR results of CYP17A1 KO rats’ adipose tissue.

a, b) Relative mRNA expression level of genes related to lipogenesis, Srebf1(SREBP-1c) and Dgat1 (DGAT). c-e) Relative mRNA expression level of genes related to lipolysis, Lipe (HSL), Prkaca (PRKACA), and Pnpla2 (ATGL). (f, g) Relative mRNA expression level of genes related to ATGL activity, Abhd5 (ABHD5) and G0s2 (G0S2). h-j) Relative mRNA expression level of genes related to glucose signaling mediated lipogenesis, Mlxipl (ChREBP), Slc2a4 (GLUT4) and Acaca (ACACA). k, l) Relative mRNA expression level of genes related to insulin-mediated glycerolipid metabolism, Irs1 (IRS1) and Pik3ca (PIK3CA). m, n) Relative mRNA expression level of genes related to adipose tissue inflammation, Il6 (IL6) and Tnf (TNFα). o, p) The data were normalized to Actb and are presented as means±SEM. Relative mRNA expression level of genes of adipokines, Agt(AGT) and Adipoq(AdipoQ). #p < 0.05 ##p < 0.01, ###p < 0.001, #### p < 0.0001, lower than wild-type, *p < 0.05 **p < 0.01, ***p < 0.001, ****p < 0.0001, higher than wild-type, using Student’s t-test (n = 12).

https://doi.org/10.1371/journal.pone.0311478.g005

Discussion

This study explored the role of the Cyp17a1 gene in obesity and its subsequent impact on metabolic diseases using a KO rat model, which was generated for the first time by CRISPR-Cas9. We conducted a detailed comparison of altered lipid and glucose metabolism between VAT and SAT. We found that despite of obesity induced by Cyp17a1 gene knockout, metabolic syndrome did not appear, and that Cyp17a1 gene knockout affected distinct metabolic shifts, underscoring its potential role in modulating disease progression in metabolic syndrome.

We observed an atypical increase in SAT in our KO rat model resulting from the deletion of the Cyp17a1 gene. Except for hyperglycemia, the Cyp17a1 KO group did not show abnormalities in insulin response or production despite obesity and resulting adipocyte hypertrophy. Furthermore, the concentration of free fatty acids in the blood did not changes, even when the diet was switched from normal chow to a high-fat diet. This suggests that deletion of the Cyp17a1 gene may suppress insulin resistance, but further research involving a comprehensive analysis of glucose-lipid metabolism including skeletal muscle and liver [40–42] is necessary to confirm the effectiveness of the Cyp17a1 KO model.

ADSCs were isolated and adipogenesis was stimulated to carry out a more detailed examination of obesity. Higher adipogenic gene expression and differentiation rate were observed in ADSCs obtained from KO females. Although it is difficult to conclude from these data whether ADSCs directly develop into adipocytes in adipose tissues in vivo, the adipogenic potential is enhanced in the adipose tissue by Cyp17a1 gene knockout compared to wild-type. Specifically, before triggering adipocyte differentiation, ADSCs from SAT in the Cyp17a1 KO group exhibited higher Klf5 mRNA expression, whereas VAT showed lower expression. Considering KLF5 facilitates the induction of adipogenic gene expression by PPARγ and C/EBPα, the findings can be interpreted as in vitro data demonstrating that Cyp17a1 knockout results in a shift in fat metabolism to subcutaneous depots (Fig 6).

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Fig 6. Graphical abstract of altered adipose tissue metabolism in Cyp17a1 KO rats.

Created in BioRender. Jang, G. (2024) BioRender.com/x87z478.

https://doi.org/10.1371/journal.pone.0311478.g006

Our findings indicate differential regulation of glucose and insulin signaling between VAT and SAT, which may contribute to distinct metabolic functions. Specifically, glucose signaling was found to be reduced in VAT, whereas it was increased in SAT. In contrast, insulin signaling was attenuated in VAT but remained relatively stable in subcutaneous adipose tissue. Interestingly, despite this stable insulin signaling in the subcutaneous tissue, we observed an upregulation of the downstream target SREBP1c. This suggests a potential redistribution of insulin signaling from VAT to SAT. Furthermore, the observed shift in insulin signaling is likely linked to changes in Klf5 gene expression, which is known to regulate lipogenesis in adipose tissue. The altered Klf5 expression may reflect an adaptive response in lipid metabolism, specifically in SAT, and contribute to differential lipid storage and processing between the two depots. Collectively, these findings suggest that the shifts in glucose and insulin signaling, along with changes in Klf5 expression, are pivotal in driving the distinct lipid metabolic profiles observed in VAT and SAT. This may provide a mechanistic basis for the differences in lipid metabolism and its associated metabolic outcomes between these two fat depots (Fig 6). As previous studies suggest that insulin resistance is caused by VAT dysfunction [15–17], it is assumed that the metabolic shift induced by Cyp17a1 deletion protects against metabolic disorders despite obesity. Also, the findings that VAT secretes fewer genes linked to inflammation and insulin resistance, such as Tnf and angiotensinogen, and that SAT does not inflame but instead secretes a significant amount of adiponectin can also be interpreted as supporting the prior assumption.

Changes in steroid hormone levels may be involved in the healthy obesity trait observed in Cyp17a1 KO rats. Numerous studies have demonstrated the connection between glucocorticoids and both insulin resistance and obesity [43–46]. Excess glucocorticoids are believed to inhibit the immune system in adipose tissue by modulating macrophages and metabolism. Since the synthesis of glucocorticoids and sex hormones depends on the CYP17A1 involved in steroidogenesis, the disruption of hormone secretion in our Cyp17a1 KO rats may contribute to their metabolically healthy obesity phenotype without insulin resistance. Consistent with our findings, another study demonstrated that steroidogenesis-related HSD11B1 deficiency prevents the development of metabolic syndrome, however, the study’s mechanism was not made explicit [47]. Further investigation into the effects of glucocorticoids and other steroid hormones on metabolism in fat, skeletal muscle, the liver, etc. in Cyp17a1 KO rats seems to be required in this respect. We cryopreserved the Cyp17a1 KO embryos and hope our Cyp17a1 KO line can be shared with other researchers and used in future studies.

In conclusion, this study demonstrated that Cyp17a1 deletion in rats via CRISPR-Cas9 induced obesity but did not lead to metabolic syndrome. Instead, a depot-specific shift from VAT to SAT appeared to protective metabolic effects. These findings may serve as a valuable framework for investigating depot-specific adipose metabolism and its contribution to obesity-related metabolic disorders. Moreover, by highlighting how alterations in adipose tissue distribution can uncouple obesity from the development of metabolic syndrome, our results provide new insights into the mechanisms underlying “metabolically healthy obesity” and may inform future strategies for preventing or managing metabolic complications associated with excess adiposity.

Supporting information

S1 Fig. Production of Cyp17a1 knockout rats.

a) Schematic image of CRISPR/Cas9 target site on rat Cyp17a1 gene. Blue line indicates start codon site and red arrow indicates cut site. b-d) PCR analysis results of F0, F1 and F2. F0 and Cyp17a1 (+/−) rats showed two bands, 877 bp and 582 bp, and wild-type rats and Cyp17a1 (−/−) rat showed one band, 877 bp upper band and 582 bp lower band each. e) Sanger sequencing result of Cyp17a1 knockout F0 rat. Box indicates deleted sequence, 295 bp. Blue letters, start codon.

https://doi.org/10.1371/journal.pone.0311478.s001

(DOCX)

S2 Fig. Sampling results of chow diet fed Cyp17a1 knockout rats.

a) Body weight measurement of chow diet fed rats age from 3 to 12 week (n = 3). b) Body weight measurement of chow diet fed rats age from 12 to 20 week (n = 6, Cyp17a1 KO group; n = 3, wild-type group). c-f’) Representative images of subcutaneous adipose tissue of chow deit fed rats. Red circles indicates inguinal (subcutaneous) adipose tissue. g-l) Sampling results of rats. (g) Body weight, (h) mass of visceral adipose tissue, (i) subcutaneous adipose tissue, (j, k) relative mass of visceral and subcutaneous adipose tissue normalized to body weight. (l) Relative subcutaneous adipose tissue mass normalized to visceral adipose tissue (n = 9, Cyp17a1 KO male; n = 8, Cyp17a1 KO female, n = 3; wild-type group). ns, not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, higher than wild-type, using Student’s t-test.

https://doi.org/10.1371/journal.pone.0311478.s002

(DOCX)

S3 Fig. Analysis of adipose tissue from Cyp17a1 knockout rats.

a, a’, b, b’) Representative images of H&E stained perigonadal adipose tissue (a, a') and subcutaneous adipose tissue (b, b’) of HFD fed male group. c, d) Adipocyte size analysis of perigonadal adipose tissue (c) and subcutaneous adipose tissue (d) from HFD fed male group. e, e’, f, f’) Representative images of H&E stained perigonadal adipose tissue (e, e') and subcutaneous adipose tissue (f, f’) of chow diet fed female group. g, h) Adipocyte size analysis of perigonadal adipose tissue (g) and subcutaneous adipose tissue (h) from chow diet fed female group. i, i’, j, j’) Representative images of H&E stained perigonadal adipose tissue (i, i') and subcutaneous adipose tissue (j, j’) of chow diet fed female group. k, l) Adipocyte size analysis of perigonadal adipose tissue (k) and subcutaneous adipose tissue (l) from chow diet fed female group. Scale bars = 100µm. #p < 0.05 ##p < 0.01, ###p < 0.001, #### p < 0.0001, lower than wild-type, *p < 0.05 **p < 0.01, ***p < 0.001, ****p < 0.0001, higher than wild-type, using Student’s t-test (n = 12).

https://doi.org/10.1371/journal.pone.0311478.s003

(DOCX)

S4 Fig. Metabolic analysis in chow diet fed Cyp17a1 knockout rats.

a, d, g) Results of insulin tolerance test (ITT) of chow diet fed female rats at 5 week age (a), 12 week (d), 20 week (g) (n = 5, Cyp17a1 knockout females at 5 week, n = 6, Cyp17a1 knockout females at the other age, n = 3, wild-type females). b, e, h) Results of insulin tolerance test (ITT) of chow diet fed male rats at 5 week age (b), 12 week (e), 20 week (h) (n = 6, Cyp17a1 knockout males, n = 3, wild-type males). c, f, i) K_ITT value of chow diet fed rats at 5 week age (c), 12 week (f), 20 week (i). j, k) Results of oral glucose tolerance test (OGTT) of chow diet fed female (j) and male (k) rats. l) Plasma insulin level of chow diet fed rats analyzed with ELISA (n = 6, Cyp17a1 knockout group; n = 3 wild-type group). m) Plasma free fatty acid level of chow diet fed rats (n = 6, Cyp17a1 knockout group; n = 3 wild-type group).

https://doi.org/10.1371/journal.pone.0311478.s004

(DOCX)

S5 Fig. Raw gel images for S1 Fig.

https://doi.org/10.1371/journal.pone.0311478.s005

(PDF)

S1 Table. Primer list used in PCR and qPCR analysis.

https://doi.org/10.1371/journal.pone.0311478.s006

(DOCX)

S2 Table. Blood biochemistry of Cyp17a1 knockout and wild-type rats with chow diet.

https://doi.org/10.1371/journal.pone.0311478.s007

(DOCX)

Acknowledgments

We are appreciated to all the members of the G. Jang lab for their valuable comments. Some of the figures in this paper were created with BioRender.com

References

1. Engin A. The Definition and Prevalence of Obesity and Metabolic Syndrome. Adv Exp Med Biol. 2017;960:1–17. pmid:28585193
- View Article
- PubMed/NCBI
- Google Scholar
2. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med. 2011;9:48. pmid:21542944
- View Article
- PubMed/NCBI
- Google Scholar
3. Koenen M, Hill MA, Cohen P, Sowers JR. Obesity, Adipose Tissue and Vascular Dysfunction. Circ Res. 2021;128(7):951–68.
- View Article
- Google Scholar
4. Smith U, Kahn BB. Adipose tissue regulates insulin sensitivity: role of adipogenesis, de novo lipogenesis and novel lipids. J Intern Med. 2016;280(5):465–75. pmid:27699898
- View Article
- PubMed/NCBI
- Google Scholar
5. Guerra Valencia J, Castillo-Paredes A, Gibaja-Arce C, Saavedra-Garcia L, Barengo NC. The Association Between Lean-to-Fat Mass Ratio and Cardiometabolic Abnormalities: An Analytical Cross-Sectional Study. J Clin Med Res. 2024;16(2–3):81–93. pmid:38550550
- View Article
- PubMed/NCBI
- Google Scholar
6. Luna-Luna M, Medina-Urrutia A, Vargas-Alarcón G, Coss-Rovirosa F, Vargas-Barrón J, Pérez-Méndez Ó. Adipose Tissue in Metabolic Syndrome: Onset and Progression of Atherosclerosis. Arch Med Res. 2015;46(5):392–407. pmid:26009250
- View Article
- PubMed/NCBI
- Google Scholar
7. Divoux A, Tordjman J, Lacasa D, Veyrie N, Hugol D, Aissat A, et al. Fibrosis in human adipose tissue: composition, distribution, and link with lipid metabolism and fat mass loss. Diabetes. 2010;59(11):2817–25. pmid:20713683
- View Article
- PubMed/NCBI
- Google Scholar
8. Kawai T, Autieri MV, Scalia R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am J Physiol Cell Physiol. 2021;320(3):C375–91. pmid:33356944
- View Article
- PubMed/NCBI
- Google Scholar
9. Richard AJ, White U, Elks CM, Stephens JM. Adipose Tissue: Physiology to Metabolic Dysfunction. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, editors. Endotext. South Dartmouth (MA). 2000.
10. Morigny P, Boucher J, Arner P, Langin D. Lipid and glucose metabolism in white adipocytes: pathways, dysfunction and therapeutics. Nat Rev Endocrinol. 2021;17(5):276–95. pmid:33627836
- View Article
- PubMed/NCBI
- Google Scholar
11. Unamuno X, Gómez-Ambrosi J, Rodríguez A, Becerril S, Frühbeck G, Catalán V. Adipokine dysregulation and adipose tissue inflammation in human obesity. Eur J Clin Invest. 2018;48(9):e12997. pmid:29995306
- View Article
- PubMed/NCBI
- Google Scholar
12. Taylor EB. The complex role of adipokines in obesity, inflammation, and autoimmunity. Clin Sci (Lond). 2021;135(6):731–52. pmid:33729498
- View Article
- PubMed/NCBI
- Google Scholar
13. Pereira S, Cline DL, Glavas MM, Covey SD, Kieffer TJ. Tissue-Specific Effects of Leptin on Glucose and Lipid Metabolism. Endocr Rev. 2021;42(1):1–28. pmid:33150398
- View Article
- PubMed/NCBI
- Google Scholar
14. Yadav A, Kataria MA, Saini V, Yadav A. Role of leptin and adiponectin in insulin resistance. Clin Chim Acta. 2013;417:80–4. pmid:23266767
- View Article
- PubMed/NCBI
- Google Scholar
15. Saponaro C, Sabatini S, Gaggini M, Carli F, Rosso C, Positano V, et al. Adipose tissue dysfunction and visceral fat are associated with hepatic insulin resistance and severity of NASH even in lean individuals. Liver Int. 2022;42(11):2418–27. pmid:35900229
- View Article
- PubMed/NCBI
- Google Scholar
16. McLaughlin T, Lamendola C, Liu A, Abbasi F. Preferential fat deposition in subcutaneous versus visceral depots is associated with insulin sensitivity. J Clin Endocrinol Metab. 2011;96(11):E1756–60. pmid:21865361
- View Article
- PubMed/NCBI
- Google Scholar
17. Yokokawa H, Fukuda H, Saita M, Goto K, Kaku T, Miyagami T, et al. An association between visceral or subcutaneous fat accumulation and diabetes mellitus among Japanese subjects. Diabetol Metab Syndr. 2021;13(1):44. pmid:33853648
- View Article
- PubMed/NCBI
- Google Scholar
18. Bluher M. Metabolically Healthy Obesity. Endocrine Reviews. 2020;41(3).
- View Article
- Google Scholar
19. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev. 2010;11(1):11–8. pmid:19656312
- View Article
- PubMed/NCBI
- Google Scholar
20. Fu Y. Adiponectin signaling and metabolic syndrome. Prog Mol Biol Transl Sci. 2014;121:293–319. pmid:24373241
- View Article
- PubMed/NCBI
- Google Scholar
21. Borel AL, Nazare JA, Smith J, Aschner P, Barter P, Van Gaal L, et al. Visceral, subcutaneous abdominal adiposity and liver fat content distribution in normal glucose tolerance, impaired fasting glucose and/or impaired glucose tolerance. Int J Obes (Lond). 2015;39(3):495–501. pmid:25179244
- View Article
- PubMed/NCBI
- Google Scholar
22. Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nat Rev Genet. 2022;23(2):120–33. pmid:34556834
- View Article
- PubMed/NCBI
- Google Scholar
23. Wajchenberg BL. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Endocr Rev. 2000;21(6):697–738. pmid:11133069
- View Article
- PubMed/NCBI
- Google Scholar
24. Burris-Hiday SD, Scott EE. Steroidogenic cytochrome P450 17A1 structure and function. Mol Cell Endocrinol. 2021;528:111261. pmid:33781841
- View Article
- PubMed/NCBI
- Google Scholar
25. Kim Y-M, Kang M, Choi J-H, Lee BH, Kim G-H, Ohn JH, et al. A review of the literature on common CYP17A1 mutations in adults with 17-hydroxylase/17,20-lyase deficiency, a case series of such mutations among Koreans and functional characteristics of a novel mutation. Metabolism. 2014;63(1):42–9. pmid:24140098
- View Article
- PubMed/NCBI
- Google Scholar
26. Wu T-T, Zheng Y-Y, Ma X, Xiu W-J, Yang H-T, Hou X-G, et al. Mutated CYP17A1 promotes atherosclerosis and early-onset coronary artery disease. Cell Commun Signal. 2023;21(1):155. pmid:37370070
- View Article
- PubMed/NCBI
- Google Scholar
27. Lin Y, Lai X, Chen B, Xu Y, Huang B, Chen Z, et al. Genetic variations in CYP17A1, CACNB2 and PLEKHA7 are associated with blood pressure and/or hypertension in She ethnic minority of China. Atherosclerosis. 2011;219(2):709–14. pmid:21963141
- View Article
- PubMed/NCBI
- Google Scholar
28. Dai W, Zhang X, Liu H, Sun Y, Fan Y, Yu Y. Two intronic variants of CYP11B1 and CYP17A1 disrupt mRNA splicing and cause congenital adrenal hyperplasia (CAH). J Pediatr Endocrinol Metab. 2020;33(9):1225–9. pmid:32687482
- View Article
- PubMed/NCBI
- Google Scholar
29. Yan H, Guo Y, Yang T-L, Zhao L-J, Deng H-W. A family-based association study identified CYP17 as a candidate gene for obesity susceptibility in Caucasians. Genet Mol Res. 2012;11(3):1967–74. pmid:22653668
- View Article
- PubMed/NCBI
- Google Scholar
30. Aherrahrou R, Kulle AE, Alenina N, Werner R, Vens-Cappell S, Bader M, et al. CYP17A1 deficient XY mice display susceptibility to atherosclerosis, altered lipidomic profile and atypical sex development. Sci Rep. 2020;10(1):8792. pmid:32472014
- View Article
- PubMed/NCBI
- Google Scholar
31. Jeon B-J, Kwon D-H, Gim G-M, Kim H-K, Lee J-H, Jang G. Stable long-term germline transmission of GFP transgenic rat via PiggyBac transposon mediated gene transfer. BMC Vet Res. 2024;20(1):275. pmid:38918814
- View Article
- PubMed/NCBI
- Google Scholar
32. Hu Y, Yu J, Cui X, Zhang Z, Li Q, Guo W, et al. Combination Usage of AdipoCount and Image-Pro Plus/ImageJ Software for Quantification of Adipocyte Sizes. Front Endocrinol (Lausanne). 2021;12:642000. pmid:34421815
- View Article
- PubMed/NCBI
- Google Scholar
33. Zhi X, Wang J, Lu P, Jia J, Shen H-B, Ning G. AdipoCount: A New Software for Automatic Adipocyte Counting. Front Physiol. 2018;9:85. pmid:29515452
- View Article
- PubMed/NCBI
- Google Scholar
34. Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9(7):671–5. pmid:22930834
- View Article
- PubMed/NCBI
- Google Scholar
35. Pu D, Tan R, Yu Q, Wu J. Metabolic syndrome in menopause and associated factors: a meta-analysis. Climacteric. 2017;20(6):583–91. pmid:29064321
- View Article
- PubMed/NCBI
- Google Scholar
36. Moreira MA, Vafaei A, da Câmara SMA, Nascimento RAdo, de Morais M do SM, Almeida M das G, et al. Metabolic syndrome (MetS) and associated factors in middle-aged women: a cross-sectional study in Northeast Brazil. Women Health. 2020;60(6):601–17. pmid:31726939
- View Article
- PubMed/NCBI
- Google Scholar
37. Pitteloud N, Hardin M, Dwyer AA, Valassi E, Yialamas M, Elahi D, et al. Increasing insulin resistance is associated with a decrease in Leydig cell testosterone secretion in men. J Clin Endocrinol Metab. 2005;90(5):2636–41. pmid:15713702
- View Article
- PubMed/NCBI
- Google Scholar
38. Fanelli G, Gevi F, Belardo A, Zolla L. Metabolic patterns in insulin-sensitive male hypogonadism. Cell Death Dis. 2018;9(6):653. pmid:29844353
- View Article
- PubMed/NCBI
- Google Scholar
39. He Q, Su G, Liu K, Zhang F, Jiang Y, Gao J, et al. Sex-specific reference intervals of hematologic and biochemical analytes in Sprague-Dawley rats using the nonparametric rank percentile method. PLoS One. 2017;12(12):e0189837. pmid:29261747
- View Article
- PubMed/NCBI
- Google Scholar
40. Dimitriadis G, Mitrou P, Lambadiari V, Maratou E, Raptis SA. Insulin effects in muscle and adipose tissue. Diabetes Res Clin Pract. 2011;93 Suppl 1:S52–9. pmid:21864752
- View Article
- PubMed/NCBI
- Google Scholar
41. Michael MD, Kulkarni RN, Postic C, Previs SF, Shulman GI, Magnuson MA, et al. Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol Cell. 2000;6(1):87–97. pmid:10949030
- View Article
- PubMed/NCBI
- Google Scholar
42. Luo J, Sobkiw CL, Hirshman MF, Logsdon MN, Li TQ, Goodyear LJ, et al. Loss of class IA PI3K signaling in muscle leads to impaired muscle growth, insulin response, and hyperlipidemia. Cell Metab. 2006;3(5):355–66. pmid:16679293
- View Article
- PubMed/NCBI
- Google Scholar
43. Beaupere C, Liboz A, Feve B, Blondeau B, Guillemain G. Molecular mechanisms of glucocorticoid-induced insulin resistance. Int J Mol Sci. 2021;22(2).
- View Article
- Google Scholar
44. Geer EB, Islam J, Buettner C. Mechanisms of glucocorticoid-induced insulin resistance: focus on adipose tissue function and lipid metabolism. Endocrinol Metab Clin North Am. 2014;43(1):75–102. pmid:24582093
- View Article
- PubMed/NCBI
- Google Scholar
45. Do TTH, Marie G, Héloïse D, Guillaume D, Marthe M, Bruno F, et al. Glucocorticoid-induced insulin resistance is related to macrophage visceral adipose tissue infiltration. J Steroid Biochem Mol Biol. 2019;185:150–62. pmid:30145227
- View Article
- PubMed/NCBI
- Google Scholar
46. Sarsenbayeva A, Pereira MJ, Nandi Jui B, Ahmed F, Dipta P, Fanni G, et al. Excess glucocorticoid exposure contributes to adipose tissue fibrosis which involves macrophage interaction with adipose precursor cells. Biochem Pharmacol. 2022;198:114976. pmid:35202577
- View Article
- PubMed/NCBI
- Google Scholar
47. Morton NM, Paterson JM, Masuzaki H, Holmes MC, Staels B, Fievet C, et al. Novel adipose tissue-mediated resistance to diet-induced visceral obesity in 11 beta-hydroxysteroid dehydrogenase type 1-deficient mice. Diabetes. 2004;53(4):931–8. pmid:15047607
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Engin A. The Definition and Prevalence of Obesity and Metabolic Syndrome. Adv Exp Med Biol. 2017;960:1–17. pmid:28585193
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med. 2011;9:48. pmid:21542944
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Koenen M, Hill MA, Cohen P, Sowers JR. Obesity, Adipose Tissue and Vascular Dysfunction. Circ Res. 2021;128(7):951–68.
View Article
Google Scholar

[10] View Article

[11] Google Scholar

[ref4] 4. Smith U, Kahn BB. Adipose tissue regulates insulin sensitivity: role of adipogenesis, de novo lipogenesis and novel lipids. J Intern Med. 2016;280(5):465–75. pmid:27699898
View Article
PubMed/NCBI
Google Scholar

[13] View Article

[14] PubMed/NCBI

[15] Google Scholar

[ref5] 5. Guerra Valencia J, Castillo-Paredes A, Gibaja-Arce C, Saavedra-Garcia L, Barengo NC. The Association Between Lean-to-Fat Mass Ratio and Cardiometabolic Abnormalities: An Analytical Cross-Sectional Study. J Clin Med Res. 2024;16(2–3):81–93. pmid:38550550
View Article
PubMed/NCBI
Google Scholar

[17] View Article

[18] PubMed/NCBI

[19] Google Scholar

[ref6] 6. Luna-Luna M, Medina-Urrutia A, Vargas-Alarcón G, Coss-Rovirosa F, Vargas-Barrón J, Pérez-Méndez Ó. Adipose Tissue in Metabolic Syndrome: Onset and Progression of Atherosclerosis. Arch Med Res. 2015;46(5):392–407. pmid:26009250
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref7] 7. Divoux A, Tordjman J, Lacasa D, Veyrie N, Hugol D, Aissat A, et al. Fibrosis in human adipose tissue: composition, distribution, and link with lipid metabolism and fat mass loss. Diabetes. 2010;59(11):2817–25. pmid:20713683
View Article
PubMed/NCBI
Google Scholar

[25] View Article

[26] PubMed/NCBI

[27] Google Scholar

[ref8] 8. Kawai T, Autieri MV, Scalia R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am J Physiol Cell Physiol. 2021;320(3):C375–91. pmid:33356944
View Article
PubMed/NCBI
Google Scholar

[29] View Article

[30] PubMed/NCBI

[31] Google Scholar

[ref9] 9. Richard AJ, White U, Elks CM, Stephens JM. Adipose Tissue: Physiology to Metabolic Dysfunction. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, editors. Endotext. South Dartmouth (MA). 2000.

[ref10] 10. Morigny P, Boucher J, Arner P, Langin D. Lipid and glucose metabolism in white adipocytes: pathways, dysfunction and therapeutics. Nat Rev Endocrinol. 2021;17(5):276–95. pmid:33627836
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref11] 11. Unamuno X, Gómez-Ambrosi J, Rodríguez A, Becerril S, Frühbeck G, Catalán V. Adipokine dysregulation and adipose tissue inflammation in human obesity. Eur J Clin Invest. 2018;48(9):e12997. pmid:29995306
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref12] 12. Taylor EB. The complex role of adipokines in obesity, inflammation, and autoimmunity. Clin Sci (Lond). 2021;135(6):731–52. pmid:33729498
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref13] 13. Pereira S, Cline DL, Glavas MM, Covey SD, Kieffer TJ. Tissue-Specific Effects of Leptin on Glucose and Lipid Metabolism. Endocr Rev. 2021;42(1):1–28. pmid:33150398
View Article
PubMed/NCBI
Google Scholar

[46] View Article

[47] PubMed/NCBI

[48] Google Scholar

[ref14] 14. Yadav A, Kataria MA, Saini V, Yadav A. Role of leptin and adiponectin in insulin resistance. Clin Chim Acta. 2013;417:80–4. pmid:23266767
View Article
PubMed/NCBI
Google Scholar

[50] View Article

[51] PubMed/NCBI

[52] Google Scholar

[ref15] 15. Saponaro C, Sabatini S, Gaggini M, Carli F, Rosso C, Positano V, et al. Adipose tissue dysfunction and visceral fat are associated with hepatic insulin resistance and severity of NASH even in lean individuals. Liver Int. 2022;42(11):2418–27. pmid:35900229
View Article
PubMed/NCBI
Google Scholar

[54] View Article

[55] PubMed/NCBI

[56] Google Scholar

[ref16] 16. McLaughlin T, Lamendola C, Liu A, Abbasi F. Preferential fat deposition in subcutaneous versus visceral depots is associated with insulin sensitivity. J Clin Endocrinol Metab. 2011;96(11):E1756–60. pmid:21865361
View Article
PubMed/NCBI
Google Scholar

[58] View Article

[59] PubMed/NCBI

[60] Google Scholar

[ref17] 17. Yokokawa H, Fukuda H, Saita M, Goto K, Kaku T, Miyagami T, et al. An association between visceral or subcutaneous fat accumulation and diabetes mellitus among Japanese subjects. Diabetol Metab Syndr. 2021;13(1):44. pmid:33853648
View Article
PubMed/NCBI
Google Scholar

[62] View Article

[63] PubMed/NCBI

[64] Google Scholar

[ref18] 18. Bluher M. Metabolically Healthy Obesity. Endocrine Reviews. 2020;41(3).
View Article
Google Scholar

[66] View Article

[67] Google Scholar

[ref19] 19. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev. 2010;11(1):11–8. pmid:19656312
View Article
PubMed/NCBI
Google Scholar

[69] View Article

[70] PubMed/NCBI

[71] Google Scholar

[ref20] 20. Fu Y. Adiponectin signaling and metabolic syndrome. Prog Mol Biol Transl Sci. 2014;121:293–319. pmid:24373241
View Article
PubMed/NCBI
Google Scholar

[73] View Article

[74] PubMed/NCBI

[75] Google Scholar

[ref21] 21. Borel AL, Nazare JA, Smith J, Aschner P, Barter P, Van Gaal L, et al. Visceral, subcutaneous abdominal adiposity and liver fat content distribution in normal glucose tolerance, impaired fasting glucose and/or impaired glucose tolerance. Int J Obes (Lond). 2015;39(3):495–501. pmid:25179244
View Article
PubMed/NCBI
Google Scholar

[77] View Article

[78] PubMed/NCBI

[79] Google Scholar

[ref22] 22. Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nat Rev Genet. 2022;23(2):120–33. pmid:34556834
View Article
PubMed/NCBI
Google Scholar

[81] View Article

[82] PubMed/NCBI

[83] Google Scholar

[ref23] 23. Wajchenberg BL. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Endocr Rev. 2000;21(6):697–738. pmid:11133069
View Article
PubMed/NCBI
Google Scholar

[85] View Article

[86] PubMed/NCBI

[87] Google Scholar

[ref24] 24. Burris-Hiday SD, Scott EE. Steroidogenic cytochrome P450 17A1 structure and function. Mol Cell Endocrinol. 2021;528:111261. pmid:33781841
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref25] 25. Kim Y-M, Kang M, Choi J-H, Lee BH, Kim G-H, Ohn JH, et al. A review of the literature on common CYP17A1 mutations in adults with 17-hydroxylase/17,20-lyase deficiency, a case series of such mutations among Koreans and functional characteristics of a novel mutation. Metabolism. 2014;63(1):42–9. pmid:24140098
View Article
PubMed/NCBI
Google Scholar

[93] View Article

[94] PubMed/NCBI

[95] Google Scholar

[ref26] 26. Wu T-T, Zheng Y-Y, Ma X, Xiu W-J, Yang H-T, Hou X-G, et al. Mutated CYP17A1 promotes atherosclerosis and early-onset coronary artery disease. Cell Commun Signal. 2023;21(1):155. pmid:37370070
View Article
PubMed/NCBI
Google Scholar

[97] View Article

[98] PubMed/NCBI

[99] Google Scholar

[ref27] 27. Lin Y, Lai X, Chen B, Xu Y, Huang B, Chen Z, et al. Genetic variations in CYP17A1, CACNB2 and PLEKHA7 are associated with blood pressure and/or hypertension in She ethnic minority of China. Atherosclerosis. 2011;219(2):709–14. pmid:21963141
View Article
PubMed/NCBI
Google Scholar

[101] View Article

[102] PubMed/NCBI

[103] Google Scholar

[ref28] 28. Dai W, Zhang X, Liu H, Sun Y, Fan Y, Yu Y. Two intronic variants of CYP11B1 and CYP17A1 disrupt mRNA splicing and cause congenital adrenal hyperplasia (CAH). J Pediatr Endocrinol Metab. 2020;33(9):1225–9. pmid:32687482
View Article
PubMed/NCBI
Google Scholar

[105] View Article

[106] PubMed/NCBI

[107] Google Scholar

[ref29] 29. Yan H, Guo Y, Yang T-L, Zhao L-J, Deng H-W. A family-based association study identified CYP17 as a candidate gene for obesity susceptibility in Caucasians. Genet Mol Res. 2012;11(3):1967–74. pmid:22653668
View Article
PubMed/NCBI
Google Scholar

[109] View Article

[110] PubMed/NCBI

[111] Google Scholar

[ref30] 30. Aherrahrou R, Kulle AE, Alenina N, Werner R, Vens-Cappell S, Bader M, et al. CYP17A1 deficient XY mice display susceptibility to atherosclerosis, altered lipidomic profile and atypical sex development. Sci Rep. 2020;10(1):8792. pmid:32472014
View Article
PubMed/NCBI
Google Scholar

[113] View Article

[114] PubMed/NCBI

[115] Google Scholar

[ref31] 31. Jeon B-J, Kwon D-H, Gim G-M, Kim H-K, Lee J-H, Jang G. Stable long-term germline transmission of GFP transgenic rat via PiggyBac transposon mediated gene transfer. BMC Vet Res. 2024;20(1):275. pmid:38918814
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref32] 32. Hu Y, Yu J, Cui X, Zhang Z, Li Q, Guo W, et al. Combination Usage of AdipoCount and Image-Pro Plus/ImageJ Software for Quantification of Adipocyte Sizes. Front Endocrinol (Lausanne). 2021;12:642000. pmid:34421815
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

[ref33] 33. Zhi X, Wang J, Lu P, Jia J, Shen H-B, Ning G. AdipoCount: A New Software for Automatic Adipocyte Counting. Front Physiol. 2018;9:85. pmid:29515452
View Article
PubMed/NCBI
Google Scholar

[125] View Article

[126] PubMed/NCBI

[127] Google Scholar

[ref34] 34. Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9(7):671–5. pmid:22930834
View Article
PubMed/NCBI
Google Scholar

[129] View Article

[130] PubMed/NCBI

[131] Google Scholar

[ref35] 35. Pu D, Tan R, Yu Q, Wu J. Metabolic syndrome in menopause and associated factors: a meta-analysis. Climacteric. 2017;20(6):583–91. pmid:29064321
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref36] 36. Moreira MA, Vafaei A, da Câmara SMA, Nascimento RAdo, de Morais M do SM, Almeida M das G, et al. Metabolic syndrome (MetS) and associated factors in middle-aged women: a cross-sectional study in Northeast Brazil. Women Health. 2020;60(6):601–17. pmid:31726939
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref37] 37. Pitteloud N, Hardin M, Dwyer AA, Valassi E, Yialamas M, Elahi D, et al. Increasing insulin resistance is associated with a decrease in Leydig cell testosterone secretion in men. J Clin Endocrinol Metab. 2005;90(5):2636–41. pmid:15713702
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref38] 38. Fanelli G, Gevi F, Belardo A, Zolla L. Metabolic patterns in insulin-sensitive male hypogonadism. Cell Death Dis. 2018;9(6):653. pmid:29844353
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

[ref39] 39. He Q, Su G, Liu K, Zhang F, Jiang Y, Gao J, et al. Sex-specific reference intervals of hematologic and biochemical analytes in Sprague-Dawley rats using the nonparametric rank percentile method. PLoS One. 2017;12(12):e0189837. pmid:29261747
View Article
PubMed/NCBI
Google Scholar

[149] View Article

[150] PubMed/NCBI

[151] Google Scholar

[ref40] 40. Dimitriadis G, Mitrou P, Lambadiari V, Maratou E, Raptis SA. Insulin effects in muscle and adipose tissue. Diabetes Res Clin Pract. 2011;93 Suppl 1:S52–9. pmid:21864752
View Article
PubMed/NCBI
Google Scholar

[153] View Article

[154] PubMed/NCBI

[155] Google Scholar

[ref41] 41. Michael MD, Kulkarni RN, Postic C, Previs SF, Shulman GI, Magnuson MA, et al. Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol Cell. 2000;6(1):87–97. pmid:10949030
View Article
PubMed/NCBI
Google Scholar

[157] View Article

[158] PubMed/NCBI

[159] Google Scholar

[ref42] 42. Luo J, Sobkiw CL, Hirshman MF, Logsdon MN, Li TQ, Goodyear LJ, et al. Loss of class IA PI3K signaling in muscle leads to impaired muscle growth, insulin response, and hyperlipidemia. Cell Metab. 2006;3(5):355–66. pmid:16679293
View Article
PubMed/NCBI
Google Scholar

[161] View Article

[162] PubMed/NCBI

[163] Google Scholar

[ref43] 43. Beaupere C, Liboz A, Feve B, Blondeau B, Guillemain G. Molecular mechanisms of glucocorticoid-induced insulin resistance. Int J Mol Sci. 2021;22(2).
View Article
Google Scholar

[165] View Article

[166] Google Scholar

[ref44] 44. Geer EB, Islam J, Buettner C. Mechanisms of glucocorticoid-induced insulin resistance: focus on adipose tissue function and lipid metabolism. Endocrinol Metab Clin North Am. 2014;43(1):75–102. pmid:24582093
View Article
PubMed/NCBI
Google Scholar

[168] View Article

[169] PubMed/NCBI

[170] Google Scholar

[ref45] 45. Do TTH, Marie G, Héloïse D, Guillaume D, Marthe M, Bruno F, et al. Glucocorticoid-induced insulin resistance is related to macrophage visceral adipose tissue infiltration. J Steroid Biochem Mol Biol. 2019;185:150–62. pmid:30145227
View Article
PubMed/NCBI
Google Scholar

[172] View Article

[173] PubMed/NCBI

[174] Google Scholar

[ref46] 46. Sarsenbayeva A, Pereira MJ, Nandi Jui B, Ahmed F, Dipta P, Fanni G, et al. Excess glucocorticoid exposure contributes to adipose tissue fibrosis which involves macrophage interaction with adipose precursor cells. Biochem Pharmacol. 2022;198:114976. pmid:35202577
View Article
PubMed/NCBI
Google Scholar

[176] View Article

[177] PubMed/NCBI

[178] Google Scholar

[ref47] 47. Morton NM, Paterson JM, Masuzaki H, Holmes MC, Staels B, Fievet C, et al. Novel adipose tissue-mediated resistance to diet-induced visceral obesity in 11 beta-hydroxysteroid dehydrogenase type 1-deficient mice. Diabetes. 2004;53(4):931–8. pmid:15047607
View Article
PubMed/NCBI
Google Scholar

[180] View Article

[181] PubMed/NCBI

[182] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Animals

Superovulation and embryo collection

gRNA synthesis, embryo electroporation and embryo transfer

Embryo cryopreservation

Genotyping

qPCR analysis

Estradiol and testosterone assay

Adipocyte size analysis

Insulin tolerance test and oral glucose tolerance test

Blood pressure measurement

Plasma insulin and free fatty acid analysis

ADSC isolation and adipogenic differentiation

Neutral lipid-positive pixel counts

Statistical analysis

Results

CYP17A1-deficient rats showed disorders of sex development and obesity with increased subcutaneous adipose tissue

CYP17A1 deficiency in rats did not induce metabolic syndrome despite their obesity and hyperglycemia

Enhanced adipogenesis in ADSCs from Cyp17a1 knockout rats

Metabolic shift from visceral to subcutaneous adipose tissue due to Cyp17a1 gene knockout

Discussion

Supporting information

S1 Fig. Production of Cyp17a1 knockout rats.

S2 Fig. Sampling results of chow diet fed Cyp17a1 knockout rats.

S3 Fig. Analysis of adipose tissue from Cyp17a1 knockout rats.

S4 Fig. Metabolic analysis in chow diet fed Cyp17a1 knockout rats.

S5 Fig. Raw gel images for S1 Fig.

S1 Table. Primer list used in PCR and qPCR analysis.

S2 Table. Blood biochemistry of Cyp17a1 knockout and wild-type rats with chow diet.

Acknowledgments

References