Saturated Fat Ingestion Promotes Lipopolysaccharide-Mediated Inflammation and Insulin Resistance in Polycystic Ovary Syndrome

Frank González; Robert V Considine; Ola A Abdelhadi; Anthony J Acton

doi:10.1210/jc.2018-01143

. 2018 Dec 26;104(3):934–946. doi: 10.1210/jc.2018-01143

Saturated Fat Ingestion Promotes Lipopolysaccharide-Mediated Inflammation and Insulin Resistance in Polycystic Ovary Syndrome

Frank González ^1,^✉, Robert V Considine ², Ola A Abdelhadi ³, Anthony J Acton ²

PMCID: PMC6364509 PMID: 30590569

Abstract

Context

Inflammation and insulin resistance (IR) are often present in polycystic ovary syndrome (PCOS).

Objective

We determined the effect of saturated fat ingestion on circulating lipopolysaccharide (LPS) and mononuclear cell (MNC) toll-like receptor-4 (TLR-4) and suppressor of cytokine signaling-3 (SOCS-3) in women with PCOS.

Design

Cross-sectional study.

Setting

Academic medical center.

Patients

Nineteen reproductive-age women with PCOS (10 lean, 9 obese) and 19 ovulatory control subjects (10 lean, 9 obese).

Main Outcome Measures

LPS and TNFα levels were measured in plasma. TLR-4 and SOCS-3 mRNA and protein content were quantified in MNC from blood collected after fasting and 2, 3, and 5 hours after saturated fat ingestion. Insulin sensitivity was derived from an oral glucose tolerance test (IS_OGTT). Androgen secretion was assessed from blood collected after fasting and 24, 48, and 72 hours after human chorionic gonadotropin (HCG) administration.

Results

Regardless of PCOS status, subjects who were obese had lipid-induced increases in circulating LPS and TLR-4 protein content compared with subjects who were lean. Lean and obese women with PCOS had lipid-induced increases in plasma TNFα and SOCS-3 mRNA and protein content compared with lean control subjects. Both PCOS groups had lower IS_OGTT and greater HCG-stimulated androgen secretion compared with control subjects. The LPS and SOCS-3 responses were negatively correlated with IS_OGTT and positively correlated with HCG-stimulated androgen secretion.

Conclusion

In PCOS, lipid-induced LPS-mediated inflammation through TLR-4 is associated with obesity and worsened by PCOS, whereas lipid-induced increases in SOCS-3 may represent an obesity-independent, TNFα-mediated mechanism of IR.

We studied the effect of lipid on LPS-mediated inflammation and TNFα-mediated IR in PCOS. We found an obesity-related LPS response worsened by PCOS and an obesity-independent mechanism of IR in PCOS.

Polycystic ovary syndrome (PCOS) is a pro-oxidant, proinflammatory state characterized by increases in reactive oxygen species, nuclear factor κB activation (NFκB) and cytokine secretion from peripheral blood mononuclear cells (MNCs) in response to glucose ingestion (1‒5). Insulin resistance (IR) is also a common finding in PCOS, resulting from defective insulin signaling that attenuates facilitative glucose transport (6, 7). Similar metabolic aberrations have been described in obesity and type 2 diabetes, and alterations in the gut microbiome have recently been implicated as a contributor to IR (8, 9).

Obese individuals have a less diverse gut microbiota enriched with bacteria that favor an increase in fatty acid absorption (8, 10). Saturated fat ingestion, in particular, promotes alterations in the gut microbiome toward that observed in obesity (11) and increases gut permeability to lipopolysaccharide (LPS), a fat-soluble component of gut-related gram-negative bacteria (12, 13). In fact, elevated circulating LPS levels have been observed in obesity and are associated with components of the metabolic syndrome (14). LPS binds to toll-like receptor-4 (TLR-4), a pathogen pattern-recognition receptor present on MNCs in the circulation and MNC-derived macrophages within tissue (15) after delivery by LPS binding protein (LBP) previously intercalated to the membrane of these cells (16). This phenomenon activates NFκB, the cardinal signal of inflammation that promotes transcription of TNFα, a known mediator of IR (17‒19). Increased TNFα expression upregulates the transcription of suppressor of cytokine-3 (SOCS-3), thereby creating a negative feedback loop that inhibits TNFα signaling (20). However, SOCS-3 can also bind tyrosine 960 of the insulin receptor, thereby preventing insulin receptor substrate-1 from binding to the insulin receptor (20). Insulin receptor substrate-1 is subsequently targeted for degradation causing truncation of the insulin signaling cascade and attenuated mobilization of GLUT 4, the glucose transport protein (21, 22).

In a recent study, obese women with PCOS had an altered gut microbiome with a preponderance of gram-negative bacteria compared with that of obese control subjects (23). A similar phenomenon was evident in lean women with PCOS compared with lean control subjects but to a much lesser extent compared with obese women with PCOS. Interestingly, circulating LBP is elevated in lean women with PCOS but similar to control subjects in overweight and obese women with PCOS (24). High LBP concentrations enhance circulating LBP-LPS complexation, thus neutralizing LPS action by impairing its ability to access membrane-bound LBP for binding to TLR-4 (16). To our knowledge, the contribution of LPS- and TLR-4–mediated inflammation to the proinflammatory state present in PCOS has never been evaluated. Similarly, the role of SOC-3 in defective insulin signaling in PCOS is unknown.

We designed a study to evaluate the effect of saturated fat ingestion on circulating LPS levels and the mRNA and protein content of TLR-4 from MNCs in women with PCOS. We also evaluated this effect on circulating TNFα levels and the mRNA and protein content of MNC-derived SOCS-3. We hypothesized that in response to saturated fat ingestion, circulating LPS and TNFα levels and the mRNA and protein content of TLR-4 and SOCS-3 are increased in women with PCOS compared with ovulatory control subjects of similar age and body mass index (BMI); and that these markers of inflammation are linked to adiposity, insulin sensitivity, levels of fasting lipids, and ovarian androgen secretion. Lean women with PCOS, representing the authentic syndrome, were evaluated separately from obese women with PCOS, who represented the superimposed effects of obesity on this disorder.

Materials and Methods

Participants

Nineteen women with PCOS (10 lean and 9 obese), 18 to 35 years of age, and 19 control subjects of similar BMI (10 lean and 9 obese), 19 to 40 years of age, volunteered for study participation. Lean subjects had a BMI between 18 and 25 kg/m². Obesity was defined as a BMI between 30 and 40 kg/m². Women with PCOS were diagnosed on the basis of oligoamenorrhea and hyperandrogenemia after excluding nonclassic congenital adrenal hyperplasia, Cushing syndrome, hyperprolactinemia, and thyroid disease. Polycystic ovaries were present on ultrasound in all subjects with PCOS. All control subjects were ovulatory, as evidenced by regular menstrual cycles lasting 25 to 35 days and a luteal-phase serum progesterone level consistent with ovulation (>5 ng/mL). All control subjects had normal circulating androgen levels and did not have any skin manifestations of androgen excess or polycystic ovaries on ultrasound.

Diabetes, inflammatory illnesses, and smoking were excluded in all subjects, although two obese women with PCOS had impaired glucose tolerance and metabolic syndrome, based on World Health Organization and Adult Treatment Panel III criteria, respectively (25, 26). Fifteen women with PCOS (six lean and nine obese) and 13 control subjects (seven lean and five obese) had a family history of type 2 diabetes. None of the subjects was taking medications for at least 6 weeks before study participation that would affect carbohydrate metabolism or immune function. No subjects exercised regularly during the 6 months before study participation. Written informed consent was obtained from all subjects according to institutional review board guidelines for the protection of human subjects.

Study design

All study subjects underwent a cream challenge test (CCT) between days 5 and 8 after the onset of menstruation and an oral glucose tolerance test (OGTT) the following day. Both tests were performed after an overnight fast of ∼12 hours. The women were given a healthy diet consisting of 50% carbohydrate, 35% fat, and 15% protein for 3 consecutive days before the CCT and after completing the CCT on the day preceding the OGTT. All subjects underwent body composition assessment on the same day as the CCT. A human chorionic gonadotropin (HCG) stimulation test was subsequently performed over 4 days beginning on the day of the OGTT.

Cream challenge test

As adapted from Deopurkar et al. (12), 100 mL of dairy cream (gourmet heavy whipping cream; Land O’ Lakes, Arden Hills, MN) was consumed by all subjects. The saturated fat content of the dairy cream preparation was 70% (28% unsaturated fat), the protein content was <2%, and the glucose content was 0%. Blood samples were collected while subjects were fasting and at 2, 3, and 5 hours after cream ingestion to quantify molecular inflammation markers from MNCs isolated as previously described (27). Plasma was isolated from these same blood samples and stored at –80°C until assayed for LPS, TNFα, and fasting lipid levels.

Oral glucose tolerance test

A 75-g glucose beverage was consumed by all subjects. Blood samples were collected while subjects were fasting and at 30, 60, 90, 120, and 180 minutes after ingestion of the glucose beverage to measure glucose and insulin levels. Plasma glucose levels were measured immediately, and insulin was measured later from plasma stored at –80°C. Insulin sensitivity was derived from the OGTT (IS_OGTT) using the Matsuda index formula: 10,000 divided by the square root of the fasting glucose level multiplied by the fasting insulin level, and that result multiplied by the product of the mean glucose level and mean insulin level (28).

HCG stimulation test

After an overnight fast of ∼12 hours, all subjects underwent baseline blood sampling at 8 am, immediately followed by administration of a 5000 IU intramuscular injection of HCG (Pregnyl; Merck & Co., Whitehouse Station, NJ). Fasting blood samples were subsequently collected at 24, 48, and 96 hours after the HCG injection. The serum isolated from these samples was stored at –80°C until assayed for testosterone, androstenedione, and 17-hydroxyprogesterone (17-OHP). Area under the curve (AUC) for androgens and 17-OHP was calculated using the trapezoidal rule (29).

Body composition assessment

Height without shoes was measured to the nearest 1.0 cm. Body weight was measured to the nearest 0.1 kg. All subjects also underwent dual-energy X-ray absorptiometry to determine percentage of total body fat, percentage of truncal fat, and R1 central abdominal fat, using the QDR 4500 Elite model scanner (Hologic, Waltham, MA), as previously described (30, 31).

Real-time PCR

Total RNA was isolated and the mRNA content of TLR-4 and SOCS-3 was quantified by real-time PCR, as previously described (32), except that an ABI Prism 7300 Sequence Detection System (Applied Biosystems, Foster City, CA) was used for the current study. Primer Express software (PE Biosystems, Foster City, CA) was used to select the primer sequences for TLR-4 (GenBank U88880.1; forward primer: 5′-TTGGGACAACCAGCCTAAAG-3′; reverse primer: 5′-TGCCATTGAAAGCAACTCTG-3′) and SOCS-3 (GenBank NM_003955; forward primer: 5′-TCACCCACAGCAAGTTTCCCGC-3′; reverse primer: 5′-GTTGACGGTCTTCCGACAGAGATGC-3′). The rRNA signal for the housekeeping gene ribosomal protein L13a was used to normalize against differences in RNA isolation and degradation, and in efficiencies of reverse transcription and PCRs using the comparative cycle threshold method.

Western blotting

The protein content of TLR-4, SOCS-3, and actin was quantified by Western blotting, as previously described, using a 1:350 dilution of a monoclonal antibody (Abcam, Cambridge, MA) against TLR-4, and a 1:500 dilution of a polyclonal antibody (Santa Cruz Biotechnology, Santa Cruz, CA) against SOCS-3 or actin (33). Densitometry after Western blotting was performed on scanned films using Carestream Molecular Imaging software, version 5.0.2.30 (Rochester, NY), and all values for TLR-4 and SOCS-3 were corrected for loading using the values obtained for actin.

Plasma and serum measurements

Plasma LPS was measured using a commercially available kit (Cambrex Limulus Amebocyte Lysate kit; Lonza, Walkersville, MD; sensitivity, 0.1 endotoxin units/mL; intraassay coefficient of variation [CV], 6.8%; interassay CV, 9.2%). Samples used to measure LPS were diluted 10-fold and processed using pyrogen-free materials in glass tubes to prevent loss of endotoxin to plastic tube walls. Plasma TNFα was measured by high-sensitivity ELISA (Quantikine; R&D Systems, Minneapolis, MN; sensitivity, 0.1 pg/mL; intraassay CV, 5.4%; interassay CV, 8.3%). Plasma glucose was measured by the glucose oxidase method (YSI; Yellow Springs, OH). Plasma insulin was measured by radioimmunoassay (Millipore, Billerica, CA; sensitivity, 2.72 µU/mL; intraassay CV, 3.8%; interassay CV, 3.2%). Plasma total cholesterol, triglycerides, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) were measured by enzymatic methods (Synchron LX20 PRO automatic analyzer, Beckman Coulter, Fullerton, CA; respective sensitivities: 25 mg/dL, 5 mg/dL, 3 mg/dL, and 8 mg/dL; intraassay CV range, 0.5% to 4.0%; interassay CV range, 1.1% to 4.5%). Serum LH, testosterone, androstenedione, and 17-OHP were measured by radioimmunoassay (Siemens, Los Angeles, CA; respective sensitivities: 0.1 IU/L, 5 ng/dL, 0.1 ng/mL, and 0.1 ng/mL; intraassay CV range, 4.1% to 6.8%; interassay CV range, 4.0% to 11.2%). The testosterone assay demonstrates good correlation with commercial liquid chromatography tandem mass spectrometry (34). Serum dehydroepiandrosterone-sulfate level was measured by chemiluminescence on a UniCel DxI 800 Immunoassay System (Beckman Coulter, Chaska, MN; sensitivity, 1 µg/dL; intraassay CV, 4.7%; interassay CV, 6.1%). All samples from each subject were measured in duplicate in the same assay at the end of the study.

Statistics

Statistical analysis was conducted using the StatView software package (SAS Institute, Cary, NC). All values were initially examined graphically for departure from normality, and the natural logarithm transformation was applied as needed. For each participant, the percent change from baseline was used to assess treatment effects on inflammation markers due to interindividual variability. The incremental AUC (iAUC) was also calculated for each inflammation marker, using the trapezoidal rule (29). Two-way ANOVA revealed significant independent effects of PCOS status (PCOS vs control) and weight class (obese vs lean) on the CCT sequential change from baseline and the iAUC of these main variables, and no significant interaction effect between PCOS status and weight class (35). Interactions were not investigated further. Data were further compared using ANOVA for multiple group comparisons (lean PCOS subjects vs lean control subjects vs obese PCOS subjects vs obese control subjects) followed by post hoc analyses using the Tukey Honestly Significant Difference test to identify the source of significance. Differences among groups in the response of inflammation markers over time during the CCT were analyzed using repeated-measures ANOVA followed by post hoc analyses. Pearson product moment correlation coefficients were calculated for correlation analyses. Data are presented as mean ± SE, and results with a two-tailed α-level of 0.05 were considered significant.

Results

Age, body composition, and blood pressure

All four groups were similar in age, height, and systolic and diastolic blood pressures (Table 1). Obese subjects had significantly (P < 0.05) higher weight, BMI, percentage of total body fat, and percentage of truncal fat and R1 fat compared with lean subjects whether or not they had PCOS. However, these measures of body composition were similar when women with PCOS were compared with control subjects of similar weight class.

Table 1.

Age, Body Composition, Endocrine, and Metabolic Characteristics of Subjects

	PCOS Subjects		Control Subjects
	Obese	Lean	Obese	Lean
Age, y	27 ± 2	26 ± 2	30 ± 2	29 ± 2
Height, cm	160.7 ± 3.6	162.2 ± 2.3	164.6 ± 2.4	165.4 ± 1.6
Body weight, kg	89.0 ± 3.9^a^,^b	58.9 ± 2.5	93.9 ± 4.0^c^,^d	63.2 ± 2.0
BMI, kg/m²	34.4 ± 0.9^a^,^b	22.3 ± 0.6	34.6 ± 0.8^c^,^d	23.1 ± 0.7
Total body fat, %	45.1 ± 1.0^a^,^b	31.1 ± 2.0	42.3 ± 0.9^c^,^d	30.6 ± 1.6
Truncal fat, %	43.7 ± 1.2^a^,^b	26.9 ± 2.5	41.5 ± 1.5^c^,^d	25.3 ± 2.0
Central fat (R1), g	2157 ± 123^a^,^b	860 ± 99	2116 ± 143^c^,^d	862 ± 61
Systolic blood pressure, mm Hg	116 ± 5	112 ± 6	126 ± 3	114 ± 4
Diastolic blood pressure, mm Hg	76 ± 2	68 ± 3	72 ± 2	70 ± 2
LPS, EU/mL	1.4 ± 0.2	1.3 ± 0.2	1.4 ± 0.1	1.3 ± 0.1
TNFα, pg/mL	2.2 ± 0.2^a^,^b	1.4 ± 0.1	2.1 ± 0.1^c^,^d	1.0 ± 0.1
Fasting glucose, mg/dL	93 ± 2^b	84 ± 2^e	90 ± 2^c	92 ± 2
2-hour glucose, mg/dL	133 ± 8^a^,^b^,^f	99 ± 1	89 ± 9	101 ± 4
Fasting insulin, µU/mL	19.0 ± 4.2^a^,^b	8.8 ± 1.6	16.5 ± 2.9^c^,^d	5.3 ± 1.3
IS_OGTT	3.2 ± 0.4^a^,^b^,^f	7.4 ± 1.3	4.9 ± 1.0^c^,^d	12.5 ± 2.3
Total cholesterol, mg/dL	179 ± 10^b^,^f	186 ± 13^e	145 ± 10^d	144 ± 6
Triglycerides, mg/dL	134 ± 25^a^,^b^,^f	79 ± 13	89 ± 13	51 ± 3
HDL-cholesterol, mg/dL	45 ± 2^a^,^b	53 ± 3	49 ± 3	53 ± 2
LDL-cholesterol, mg/dL	111 ± 8^b^,^f	121 ± 13^e	78 ± 8^d	81 ± 6
LH, mIU/mL	13.7 ± 2.0^b^,^f	14.5 ± 2.0^e	5.3 ± 0.7^d	6.2 ± 0.6
Testosterone, ng/dL	69.2 ± 8.8^b^,^f	53.0 ± 4.5^e	20.4 ± 4.1^d	29.5 ± 5.4
Androstenedione, ng/mL	3.9 ± 0.3^b^,^f	3.8 ± 0.2^e	2.1 ± 0.2^d	2.0 ± 0.2
DHEA-S, µg/dL	209 ± 30	47 ± 32	153 ± 23^d	222 ± 21
Testosterone, AUC	7131 ± 1025^b^,^f	5678 ± 674^e	3700 ± 201^d	3437 ± 495
Androstendione, AUC	576 ± 51^b^,^f	506 ± 31^e	329 ± 37^d	576 ± 51
17-OHP, AUC	24,152 ± 2590^b^,^f	20,897 ± 3264^e	9836 ± 590^d	9995 ± 1237

Open in a new tab

Values are expressed as mean ± SE. Conversion factors to SI units: testosterone ×3.467 (nmol/L), androstenedione ×3.492 (nmol/L), DHEA-S ×0.002714 (μmol/L), glucose ×0.0551 (mmol/L), and insulin ×7.175 (pmol/L).

Abbreviations: AUC, HCG-stimulated AUC; DHEA-S, dehydroepiandrosterone-sulfate; EU, endotoxin units.

^{^a}

PCOS obese vs PCOS lean subjects, P < 0.05.

^{^b}

PCOS obese vs control lean subjects, P < 0.04.

^{^c}

Control obese subjects vs control lean subjects, P < 0.006.

^{^d}

PCOS lean vs control obese subjects, P < 0.05.

^{^e}

PCOS lean vs control lean subjects, P < 0.05.

^{^f}

PCOS obese vs control obese subjects, P < 0.05.

Plasma LPS and TLR-4 mRNA and protein content

Basal plasma LPS levels were similar in all four groups (Table 1). In response to saturated fat ingestion, the change from baseline in plasma LPS and MNC-derived TLR-4 mRNA and protein content decreased in lean subjects and was significantly (P < 0.02) different compared with the increase observed in obese subjects after 2 and 3 hours whether or not they had PCOS (Fig. 1). The response in all three inflammatory markers reached a maximum after 3 hours in all four groups and returned to baseline in the lean groups and in obese control subjects after 5 hours. Obese women with PCOS had significantly (P < 0.02) greater responses in plasma LPS and MNC-derived TLR-4 protein content compared with obese control subjects after 2 and 3 hours, and significantly (P < 0.02) greater residual responses in all three inflammatory markers compared with the other three groups after 5 hours.

Figure 1. — Comparison of the four study groups regarding the change from baseline (%) in (A) plasma LPS level, (B) MNC-derived TLR-4 mRNA content, and (C) TLR-4 protein content from blood samples collected while subjects were fasting and at 2, 3, and 5 hours after saturated fat ingestion. (C) Representative Western blots show the change in quantity of TLR-4 and actin in MNC homogenates before and after saturated fat ingestion. The samples used to quantify proteins by densitometry were run on the same gel. Obese women with PCOS and obese control subjects exhibited greater responses in plasma LPS (*P < 0.0001), TLR-4 mRNA content (*P < 0.03), and TLR-4 protein content (*P < 0.0001) compared with lean women with PCOS and lean control subjects at 2 and 3 hours after ingesting saturated fat. Obese women with PCOS exhibited greater responses in plasma LPS levels (^†P < 0.009) and TLR-4 protein content (^†P < 0.02) compared with obese control subjects at 2 and 3 hours after ingesting saturated fat. Obese women with PCOS exhibited greater residual responses in plasma LPS level (^‡P < 0.0001), TLR-4 mRNA content (^†P < 0.02), and TLR-4 protein content (^‡P < 0.0001) compared with lean women with PCOS, and control subjects who were lean or obese at 5 hours after ingesting saturated fat.

The iAUC for plasma LPS and MNC-derived TLR-4 mRNA and protein content also decreased in lean subjects and was significantly (P < 0.04) different compared with the increase observed in obese subjects whether or not they had PCOS (Fig. 2). Obese women with PCOS exhibited a significantly (P < 0.0007) greater iAUC for plasma LPS and TLR-4 protein content compared with obese control subjects.

Figure 2. — Comparison of the four study groups regarding the lipid-induced iAUC in response to saturated fat ingestion for (A) plasma LPS levels, MNC-derived (B) TLR-4 mRNA content and (C) TLR-4 protein content, (D) plasma TNFα levels, and MNC-derived (E) SOCS-3 mRNA content and (F) SOCS-3 protein content. Obese control subjects and obese women with PCOS had a greater iAUC for plasma LPS (*P < 0.04; ^†P < 0.001), TLR-4 mRNA content (*P < 0.02; ^†P < 0.007), and TLR-4 protein content (*P < 0.0001; ^†P < 0.0001), compared with lean women with PCOS and lean control subjects. Obese women with PCOS exhibited a greater iAUC for plasma LPS (P < 0.0007) and TLR-4 protein content (P < 0.0001) compared with obese control subjects. Lean women with PCOS, obese control subjects, and obese women with PCOS had a greater iAUC for plasma TNFα (*P < 0.01; ^†P < 0.03), SOCS-3 mRNA content (*P < 0.03;^†P < 0.008), and SOCS-3 protein content (*P < 0.0001; ^†P < 0.0001), compared with lean control subjects. Obese women with PCOS had a greater iAUC for SOCS-3 mRNA content (^‡P < 0.05) and SOCS-3 protein content (^‡P < 0.005) compared with obese control subjects.

Plasma TNFα and SOCS-3 mRNA and protein content

Basal plasma TNFα levels were significantly (P < 0.0001) higher in obese subjects whether or not they had PCOS (Table 1). In response to saturated fat ingestion, the change from baseline in plasma TNFα and MNC-derived SOCS-3 mRNA and protein content decreased in lean control subjects and was significantly (P < 0.05) different compared with the increase observed in lean and obese women with PCOS and obese control subjects after 2 and 3 hours (Fig. 3). The SOCS-3 mRNA and protein content response reached a maximum after 3 hours in all four groups and returned to baseline in the lean groups and in obese control subjects after 5 hours. Obese women with PCOS exhibited significantly (P < 0.05) greater responses in SOCS-3 protein content compared with obese control subjects after 2 and 3 hours, and significantly (P < 0.0001) greater residual responses in SOCS-3 mRNA and protein content compared with the other three groups after 5 hours.

Figure 3. — Comparison of the four study groups of the change from baseline (%) in (A) plasma TNFα levels, MNC-derived (B) SOCS-3 mRNA content, and (C) SOCS-3 protein content from blood samples collected while subjects fasted and at 2, 3, and 5 hours after saturated fat ingestion. (C) Representative Western blots show the change in quantity of SOCS-3 and actin in MNC homogenates in samples collected before and after saturated fat ingestion. The samples used to quantify proteins by densitometry were run on the same gel. Lean and obese women with PCOS and obese control subjects exhibited greater responses in plasma TNFα (*P < 0.03), SOCS-3 mRNA content (*P < 0.005), and SOCS-3 protein content (*P < 0.0001) compared with lean control subjects at 2 and 3 hours after ingesting saturated fat. Obese women with PCOS had a greater SOCS-3 protein content response (^†P < 0.05) compared with obese control subjects at 2 and 3 hours after ingesting saturated fat. Obese women with PCOS had greater residual responses in SOCS-3 mRNA content (^†P < 0.0001) and SOCS-3 protein content (^‡P < 0.0001) compared with lean women with PCOS, and control subjects who were lean or obese at 5 hours after ingesting saturated fat.

The iAUC for plasma TNFα and MNC-derived SOCS-3 mRNA and protein content decreased in lean control subjects and was significantly (P < 0.03) different compared with the increase observed in lean and obese women with PCOS and obese control subjects (Fig. 2). Obese women with PCOS exhibited a significantly (P < 0.05) greater iAUC for SOCS-3 mRNA and protein content compared with obese control subjects.

Insulin sensitivity and fasting lipids

IS_OGTT was significantly lower (P < 0.05) in subjects who were obese compared with lean control subjects and in lean women with PCOS compared with lean control subjects (Table 1). Plasma cholesterol and LDL were significantly (P < 0.05) higher in women with PCOS compared with control subjects regardless of body composition status. In obese women with PCOS, plasma triglycerides were significantly (P < 0.05) higher compared with those of the other three groups, and plasma HDL was significantly (P < 0.05) lower compared with lean subjects whether or not they had PCOS. Nevertheless, mean lipid levels were clinically normal in all four groups.

Basal hormone levels and HCG-stimulated androgen and 17-OHP responses

Serum levels of LH, testosterone, and androstenedione were significantly (P < 0.05) higher in women with PCOS compared with control subjects regardless of body composition status. However, dehydroepiandrosterone-sulfate levels were similar in all four groups (Table 1). The AUC for the HCG-stimulated responses of testosterone, androstenedione, and 17-OHP were significantly (P < 0.05) higher in women with PCOS compared with that of control subjects regardless of weight class.

Correlations

BMI, percentage of total body fat, percentage of truncal fat and R1 fat were positively correlated with the iAUC for plasma LPS levels, TLR-4 mRNA and protein content, and SOCS-3 mRNA and protein content for the combined groups and separately in women with PCOS and control subjects (Table 2). These same adiposity measures were also positively correlated with the plasma TNFα iAUC for the combined groups and in control subjects.

Table 2.

Pearson Correlations of the Incremental Area Under the Curve for Inflammation Markers During the Cream Challenge Test With Measures of Adiposity and Insulin Sensitivity

		Plasma LPS iAUC	TLR-4 mRNA Content iAUC	TLR-4 Protein Content iAUC	Plasma TNFα iAUC	SOS-3 mRNA Content iAUC	SOCS-3 Protein Content iAUC
Combined groups
BMI, kg/m²	r	0.62	0.62	0.76	0.33	0.44	0.44
BMI, kg/m²	P	****	****	****	*	***	***
Total body fat, %	r	0.59	0.52	0.75	0.39	0.35	0.50
Total body fat, %	P	****	****	****	**	**	***
Truncal fat, %	r	0.59	0.54	0.76	0.35	0.36	0.48
Truncal fat, %	P	****	****	****	*	*	**
Central fat (R1), g	r	0.65	0.64	0.78	0.33	0.52	0.48
Central fat (R1), g	P	****	****	****	*	****	***
IS_OGTT	r	−0.39	−0.40	−0.57	−0.32	−0.42	−0.56
IS_OGTT	P	*	*	****	*	***	****
PCOS
BMI, kg/m²	r	0.71	0.68	0.91	0.22	0.51	0.47
BMI, kg/m²	P	****	***	****	NS	*	*
Total body fat, %	r	0.62	0.60	0.81	0.28	0.30	0.61
Total body fat, %	P	***	***	****	NS	NS	***
Truncal fat, %	r	0.58	0.58	0.83	0.27	0.52	0.54
Truncal fat, %	P	***	***	****	NS	*	*
Central fat (R1), g	r	0.67	0.60	0.87	0.17	0.51	0.52
Central fat (R1), g	P	***	***	****	NS	*	*
IS_OGTT	r	−0.39	−0.32	−0.63	−0.06	−0.25	−0.23
IS_OGTT	P	NS	NS	***	NS	NS	NS
Control subjects
BMI, kg/m²	r	0.66	0.55	0.63	0.50	0.55	0.79
BMI, kg/m²	P	***	*	***	*	*	****
Total body fat, %	r	0.58	0.52	0.69	0.48	0.47	0.69
Total body fat, %	P	***	*	***	*	*	***
Truncal fat, %	r	0.70	0.49	0.69	0.60	0.51	0.66
Truncal fat, %	P	****	*	***	***	*	***
Central fat (R1), g	r	0.79	0.66	0.71	0.60	0.73	0.74
Central fat (R1), g	P	****	*	****	***	****	****
IS_OGTT	r	−0.51	−0.49	−0.54	−0.49	−0.50	−0.58
IS_OGTT	P	*	*	*	*	*	*

Open in a new tab

*P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.

Abbreviation: NS, not significant.

IS_OGTT was negatively correlated with BMI (r = −0.53; P < 0.0006), percentage of total body fat (r = 0.53; P < 0.0006), percentage of truncal fat (r = −0.58; P < 0.0002) and R1 fat (r = −0.54; P < 0.0004) for the combined groups. IS_OGTT was also negatively correlated with the iAUC for plasma LPS, TLR-4 mRNA and protein content, plasma TNFα, and SOCS-3 mRNA and protein content for the combined groups and in control subjects, and with TLR-4 protein content in women with PCOS (Table 2).

For the combined groups, plasma triglyceride levels were positively correlated with plasma LPS iAUC (r = 0.38; P < 0.02) and the iAUC for the protein content of TLR-4 (r = 0.50; P < 0.002) and SOCS-3 (r = 0.43; P < 0.009); and plasma HDL was negatively correlated with the iAUC for plasma LPS (r = −0.33; P < 0.05) and TLR-4 protein content (r = −0.53; P < 0.0006). Plasma HDL was negatively correlated with TLR-4 protein content iAUC (r = −0.55; P < 0.02) in women with PCOS. Plasma triglycerides were positively correlated with the iAUC for the protein content of TLR-4 (r = 0.75; P < 0.0003) and SOCS-3 (r = 0.65; P < 0.004) in control subjects.

For the combined groups, there were positive correlations between basal LH and SOCS-3 protein content, basal androstenedione and SOCS-3 mRNA content, HCG-stimulated androstenedione AUC, and the iAUC for plasma LPS, TLR-4 protein content, and SOCS-3 mRNA content, along with HCG-stimulated 17-OHP AUC and SOC-3 mRNA and protein content (Table 3). For the combined groups and in women with PCOS, basal testosterone and HCG-stimulated testosterone AUC were positively correlated with plasma LPS iAUC, and basal androstenedione and HCG-stimulated androstenedione AUC were positively correlated with the SOCS-3 protein content iAUC. The SOCS-3 mRNA content iAUC was positively correlated with basal LH in women with PCOS, and with basal androstenedione in control subjects (r = 0.59; P < 0.02).

Table 3.

Pearson Correlations of the Incremental Area Under the Curve for Inflammation Markers During the Cream Challenge Test With Circulating LH and Androgens

		Plasma LPS iAUC	TLR-4 mRNA Content iAUC	TLR-4 Protein Content iAUC	Plasma TNFα iAUC	SOCS-3 mRNA Content iAUC	SOCS-3 Protein Content iAUC
Combined groups
LH, iU/mL	r	0.20	0.14	0.09	0.05	0.03	0.44
LH, iU/mL	P	NS	NS	NS	NS	NS	***
Testosterone, ng/dL	r	0.34	0.14	0.15	0.14	0.09	0.29
Testosterone, ng/dL	P	*	NS	NS	NS	NS	NS
Androstenedione, ng/mL	r	0.24	0.13	0.23	0.20	0.48	0.55
Androstenedione, ng/mL	P	NS	NS	NS	NS	***	****
DHEA-S, μg/dL	r	0.15	0.15	0.34	0.03	0.20	0.04
DHEA-S, μg/dL	P	NS	NS	NS	NS	NS	NS
Testosterone AUC^a	r	0.49	0.11	0.26	0.14	0.18	0.34
Testosterone AUC^a	P	***	NS	NS	NS	NS	*
Androstenedione AUC^a	r	0.38	0.24	0.33	0.26	0.46	0.49
Androstenedione AUC^a	P	**	NS	*	NS	***	***
17OHP AUC	r	0.02	0.09	0.14	0.19	0.34	0.36
17OHP AUC	P	NS	NS	NS	NS	*	*
PCOS
LH, iU/mL	r	0.04	0.19	0.09	0.30	0.57	0.18
LH, iU/mL	P	NS	NS	NS	NS	*	NS
Testosterone, ng/dL	r	0.39	0.02	0.22	0.28	0.25	0.14
Testosterone, ng/dL	P	*	NS	NS	NS	NS	NS
Androstenedione, ng/mL	r	0.14	0.07	0.04	0.09	0.24	0.52
Androstenedione, ng/mL	P	NS	NS	NS	NS	NS	*
DHEA-S, μg/dL	r	−0.23	−0.28	−0.25	−0.07	−0.61	−0.09
DHEA-S, μg/dL	P	NS	NS	NS	NS	***	NS
Testosterone AUC^a	r	0.51	0.26	0.26	0.44	0.01	0.003
Testosterone AUC^a	P	*	NS	NS	*	NS	NS
Androstenedione AUC^a	r	0.21	0.21	0.27	0.13	0.16	0.41
Androstenedione AUC^a	P	NS	NS	NS	NS	NS	*
17OHP AUC^a	r	−0.33	−0.29	−0.07	−0.06	0.02	0.24
17OHP AUC^a	P	NS	NS	NS	NS	NS	NS

Open in a new tab

*P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.

Abbreviations: DHEA-S, dehydroepiandrosterone-sulfate; NS, not significant.

^{^a}

HCG-stimulated AUC.

Discussion

Our data clearly show that in PCOS, increases in circulating LPS and TLR-4–related inflammation emanating from MNCs in response to saturated fat ingestion only occur in the presence of obesity. Obese subjects, whether or not they had PCOS, had lipid-induced increases in plasma LPS and TNFα levels, and MNC-derived TLR-4 and SOC-3 gene expression. However, obese women with PCOS had the highest plasma LPS and TLR-4 protein content responses, indicative of an obesity-related phenomenon that is worsened by PCOS. Furthermore, lean women with PCOS had lipid-induced increases in plasma TNFα and SOC-3 gene expression compared with lean control subjects, implicating TNFα-mediated SOCS-3 action as a potential mechanism of IR in PCOS that is independent of obesity. Plasma LPS and SOCS-3 gene expression were negatively associated with insulin sensitivity and positively associated with basal and HCG-stimulated androgen secretion, lending further support to the concept that lipid-stimulated inflammation may be involved in promoting IR and hyperandrogenism in PCOS. The positive association between circulating and molecular markers of inflammation and measures of adiposity also suggests that in PCOS, excess adipose tissue is a contributor to the inflammatory load and an additional modulator of insulin action.

Lean, healthy, reproductive-age women exhibited suppression of MNC-derived inflammation after saturated fat ingestion, which may be the in vivo norm for this population. The responses of plasma LPS, TLR-4 mRNA and protein content, plasma TNFα, and SOCS-3 mRNA and protein content were suppressed in lean control subjects. We previously reported a similar response pattern after glucose ingestion for MNC-derived NFκB activation and associated mediators of inflammation in normal reproductive-age women (2–5, 36). In contrast, studies of lean humans that included men and older individuals reported pro-oxidant, proinflammatory responses to ingestion of glucose, saturated fat, and, to a lesser extent, protein (37). Most notably, one study of this latter cohort demonstrated increases in circulating LPS and TLR-4 expression only in response to ingestion of saturated fat, but not to glucose (12), which highlights the more profound role of saturated fat in the induction of postprandial inflammation. Thus, lean, healthy, reproductive-age women are protected from the proinflammatory effect of saturated fat ingestion, thereby avoiding suboptimal insulin signaling to maintain adequate glucose disposal.

Lean women with PCOS are in a proinflammatory state promoted by saturated fat ingestion. Plasma TNFα and SOCS-3 mRNA and protein content increased after saturated fat ingestion in lean women with PCOS compared with lean control subjects. This finding represents a potential TNFα-mediated inflammatory mechanism of IR in PCOS and is corroborated by the negative association of SOCS-3 mRNA and protein content responses with insulin sensitivity in women with PCOS. In contrast, LPS does not appear to mediate inflammation in lean women with PCOS, because plasma LPS and MNC-derived TLR-4 mRNA and protein content were suppressed in this group after saturated fat ingestion, thereby mimicking the responses observed in lean control subjects. This latter finding suggests that the modest gut microbiome alteration described previously in lean women with PCOS (23) has no effect on systemic and MNC-derived inflammation. The elevated circulating LBP levels in lean women with PCOS (24) may contribute to this phenomenon through LPS sequestration within circulating LBP-LPS complexes, thereby preventing LPS access to membrane-bound LBP for TLR-4 binding (16). Thus, women with PCOS display a distinct proinflammatory risk profile incited by saturated fat ingestion that promotes IR yet is unrelated to circulating LPS and independent of obesity.

Obese women with PCOS are in an even greater proinflammatory state perpetuated by saturated fat ingestion. This was evident in the present study by the increases in plasma LPS and TNFα, and MNC-derived TLR-4 and SOCS-3 mRNA and protein content after saturated fat ingestion in obese subjects compared with lean subjects regardless of PCOS status. The even greater LPS and TLR-4 protein content responses observed in obese women with PCOS compared with obese control subjects may be related to the preponderance of gram-negative bacteria in the gut microbiome of these individuals (22). This phenomenon favors a systemic and MNC-related proinflammatory milieu that promotes defective insulin signaling and IR, as described previously in obesity (12, 38–40). This is corroborated in our study by the inverse relationship of the responses of plasma LPS and TNFα, and MNC-derived TLR-4 and SOCS-3 mRNA and protein content with insulin sensitivity. Thus, it appears that obesity is the main driver of lipid-induced increases in circulating LPS and MNC-derived TLR-4 gene expression with an even greater LPS-mediated inflammatory response when obesity is combined with PCOS. Research with a larger sample size is merited to better evaluate the potential interaction between PCOS and obesity on the lipid-induced responses of LPS and TLR-4.

In PCOS, inflammation triggered by saturated fat ingestion is linked to adiposity. In the present study, plasma LPS iAUC and lipid-stimulated mediators of inflammation were positively associated with measures of adiposity, especially abdominal adiposity for the combined groups and in women with PCOS. Migration of MNCs into the stromal-vascular compartment of excess adipose tissue as a result of hypoxia-related cell death incites oxidative stress (41, 42). TNFα is subsequently produced by MNC-derived macrophages and serves as a paracrine stimulator of adipocyte TNFα production (43). Measures of abdominal adiposity are also negatively associated with insulin sensitivity. Thus, circulating MNCs and excess adipose tissue may be joint contributors to systemic inflammation and IR in PCOS.

In PCOS, inflammation triggered by saturated fat ingestion is also linked to dyslipidemia. In the present study, plasma LPS iAUC and the iAUC for the protein content of TLR-4 and SOCS-3 were positively associated with plasma triglyceride levels for the combined groups, and TLR-4 protein content iAUC was negatively associated with plasma HDL level for the combined groups and in women with PCOS. Indeed, LPS and multiple cytokines, including TNFα, stimulate hepatic fatty acid synthesis, adipose tissue lipolysis, and fatty acid transport to the liver, thereby increasing hepatic triglyceride and triglyceride-rich very-low-density lipoprotein (VLDL) production and secretion into the circulation (44). The abundance of VLDL per se promotes the transfer of triglyceride from VLDL to LDL, which can subsequently be hydrolyzed by hepatic lipase to small, dense LDL. This latter form of LDL is proatherogenic, because it can easily penetrate the blood vessel wall and is more readily oxidized for enhanced uptake by foamy macrophages within atherosclerotic plaques (45). LPS and TNFα also lower circulating HDL and cause structural alterations in HDL that reduce its ability to scavenge cholesterol from foamy macrophages (46). In our study, cholesterol and LDL levels were higher in women with PCOS regardless of weight class, whereas triglyceride levels were higher and HDL levels were lower in obese women with PCOS, in particular. Thus, lipid-induced inflammation may be a potent driver of dyslipidemia in PCOS, particularly when combined with obesity, with inflammation and the abnormal lipid profile working in concert to promote atherogenesis at a young age.

In PCOS, inflammation stimulated by saturated fat ingestion may directly promote hyperandrogenism. Basal levels of LH and androgens along with the HCG-stimulated androgen secretion were all positively associated with various lipid-stimulated inflammation markers for the combined groups and in women with PCOS in the present study. These findings corroborate similar findings from our previous studies (1–5, 47). Although the relationship with LH suggests a central effect of inflammation on ovarian androgen production, local effects are well characterized. Saturated fat ingestion increases the number of MNC-derived macrophages within the ovary (48). TNFα secreted from macrophages can promote serine phosphorylation that may increase the activity of the 17,20-lyase androgen-producing arm of CYP17 (49). TNFα also stimulates theca cell proliferation (50). In addition, chronic suppression of inflammation with salicylate therapy reduces basal and HCG-stimulated androgen secretion in lean insulin-sensitive women with PCOS (51). Thus, an inflammatory response from MNCs trafficking into the polycystic ovary manifested by lipid-induced TLR-4 gene expression and subsequent TNFα secretion may promote the proliferation and steroidogenic activity of theca cells to stimulate excess ovarian androgen production.

In conclusion, saturated fat ingestion promoted increases in circulating LPS levels and TLR-4 gene expression in obese reproductive-age women that were even greater when PCOS was present. Saturated fat ingestion also stimulated increased circulating TNFα levels and SOCS-3 gene expression in women with PCOS regardless of weight class. Thus, the lipid-induced increase in LPS-mediated inflammation is an obesity-related phenomenon made worse by PCOS. In contrast, the lipid-induced increase in SOCS-3 gene expression may represent a potential TNFα-mediated inflammatory mechanism of IR in PCOS that is independent of obesity. These proinflammatory phenomena highlight the separate and distinct impacts of circulating MNCs and excess adipose tissue in the development of IR, dyslipidemia, and hyperandrogenism in PCOS.

Acknowledgments

We thank the nursing staff of the Indiana Clinical and Translational Sciences Institute Clinical Research Center for supporting the implementation of the study and assisting with data collection. We thank Merck Sharp & Dohme for generously donating the Pregnyl used in this study. This paper was presented in part at the 61st meeting of the Society for Reproductive Investigation, Florence, Italy, 26–29 March 2014, and at the 72nd meeting of the American Society for Reproductive Medicine, Salt Lake City, Utah, 15–19 October 2016.

Financial Support: This research was supported by Grant R01 DK107605 to F.G. from the National Institutes of Health (NIH); the Indiana Clinical and Translational Sciences Institute Clinical Research Center, which is funded in part by NIH Grant UL1TR001108, a Clinical and Translational Sciences Award from the National Center for Advancing Translational Sciences; and the Indiana University Center for Diabetes and Metabolic Diseases, funded by NIH Grant P30 DK097512. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Clinical Trial Information: ClinicalTrials.gov NCT01489319 (registered 9 December 2011).

Disclosure Summary: The authors have nothing to disclose.

Glossary

Abbreviations:

17-OHP: 17-hydroxyprogesterone
AUC: area under the curve
BMI: body mass index
CCT: cream challenge test
CV: coefficient of variation
HCG: human chorionic gonadotropin
HDL: high-density lipoprotein
iAUC: incremental area under the curve
IR: insulin resistance
IS_OGTT: insulin sensitivity derived from an oral glucose tolerance test
LBP: lipopolysaccharide binding protein
LDL: low-density lipoprotein
LPS: lipopolysaccharide
MNC: mononuclear cell
NFκB: nuclear factor κB
OGTT: oral glucose tolerance test
PCOS: polycystic ovary syndrome
SOCS-3: suppressor of cytokine signaling-3
TLR-4: toll-like receptor-4
VLDL: very-low-density lipoprotein

References

1. González F, Rote NS, Minium J, Kirwan JP. Reactive oxygen species-induced oxidative stress in the development of insulin resistance and hyperandrogenism in polycystic ovary syndrome. J Clin Endocrinol Metab. 2006;91(1):336–340. [DOI] [PubMed] [Google Scholar]
2. González F, Sia CL, Shepard MK, Rote NS, Minium J. Hyperglycemia-induced oxidative stress is independent of excess abdominal adiposity in normal-weight women with polycystic ovary syndrome. Hum Reprod. 2012;27(12):3560–3568. [DOI] [PMC free article] [PubMed] [Google Scholar]
3. González F, Rote NS, Minium J, Kirwan JP. Increased activation of nuclear factor kappaB triggers inflammation and insulin resistance in polycystic ovary syndrome. J Clin Endocrinol Metab. 2006;91(4):1508–1512. [DOI] [PubMed] [Google Scholar]
4. González F, Sia CL, Shepard MK, Rote NS, Minium J. Inflammation in response to glucose ingestion is independent of excess abdominal adiposity in normal-weight women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2012;97(11):4071–4079. [DOI] [PMC free article] [PubMed] [Google Scholar]
5. González F, Sia CL, Shepard MK, Rote NS, Minium J. The altered mononuclear cell-derived cytokine response to glucose ingestion is not regulated by excess adiposity in polycystic ovary syndrome. J Clin Endocrinol Metab. 2014;99(11):E2244–E2251. [DOI] [PMC free article] [PubMed] [Google Scholar]
6. Dunaif A, Segal KR, Futterweit W, Dobrjansky A. Profound peripheral insulin resistance, independent of obesity, in polycystic ovary syndrome. Diabetes. 1989;38(9):1165–1174. [DOI] [PubMed] [Google Scholar]
7. Corbould A, Kim YB, Youngren JF, Pender C, Kahn BB, Lee A, Dunaif A. Insulin resistance in the skeletal muscle of women with PCOS involves intrinsic and acquired defects in insulin signaling. Am J Physiol Endocrinol Metab. 2005;288(5):E1047–E1054. [DOI] [PubMed] [Google Scholar]
8. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–1023. [DOI] [PubMed] [Google Scholar]
9. Schwiertz A, Taras D, Schäfer K, Beijer S, Bos NA, Donus C, Hardt PD. Microbiota and SCFA in lean and overweight healthy subjects. Obesity (Silver Spring). 2010;18(1):190–195. [DOI] [PubMed] [Google Scholar]
10. Bäckhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, Semenkovich CF, Gordon JI. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci USA. 2004;101(44):15718–15723. [DOI] [PMC free article] [PubMed] [Google Scholar]
11. Fava F, Gitau R, Griffin BA, Gibson GR, Tuohy KM, Lovegrove JA. The type and quantity of dietary fat and carbohydrate alter faecal microbiome and short-chain fatty acid excretion in a metabolic syndrome ‘at-risk’ population. Int J Obes. 2013;37(2):216–223. [DOI] [PubMed] [Google Scholar]
12. Deopurkar R, Ghanim H, Friedman J, Abuaysheh S, Sia CL, Mohanty P, Viswanathan P, Chaudhuri A, Dandona P. Differential effects of cream, glucose, and orange juice on inflammation, endotoxin, and the expression of Toll-like receptor-4 and suppressor of cytokine signaling-3. Diabetes Care. 2010;33(5):991–997. [DOI] [PMC free article] [PubMed] [Google Scholar]
13. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM, Burcelin R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes. 2008;57(6):1470–1481. [DOI] [PubMed] [Google Scholar]
14. Lassenius MI, Pietiläinen KH, Kaartinen K, Pussinen PJ, Syrjänen J, Forsblom C, Pörsti I, Rissanen A, Kaprio J, Mustonen J, Groop PH, Lehto M; FinnDiane Study Group . Bacterial endotoxin activity in human serum is associated with dyslipidemia, insulin resistance, obesity, and chronic inflammation. Diabetes Care. 2011;34(8):1809–1815. [DOI] [PMC free article] [PubMed] [Google Scholar]
15. Xu XH, Shah PK, Faure E, Equils O, Thomas L, Fishbein MC, Luthringer D, Xu XP, Rajavashisth TB, Yano J, Kaul S, Arditi M. Toll-like receptor-4 is expressed by macrophages in murine and human lipid-rich atherosclerotic plaques and upregulated by oxidized LDL. Circulation. 2001;104(25):3103–3108. [DOI] [PubMed] [Google Scholar]
16. Gutsmann T, Müller M, Carroll SF, MacKenzie RC, Wiese A, Seydel U. Dual role of lipopolysaccharide (LPS)-binding protein in neutralization of LPS and enhancement of LPS-induced activation of mononuclear cells. Infect Immun. 2001;69(11):6942–6950. [DOI] [PMC free article] [PubMed] [Google Scholar]
17. Covert MW, Leung TH, Gaston JE, Baltimore D. Achieving stability of lipopolysaccharide-induced NF-kappaB activation. Science. 2005;309(5742):1854–1857. [DOI] [PubMed] [Google Scholar]
18. Barnes PJ, Karin M. Nuclear factor-kappaB: a pivotal transcription factor in chronic inflammatory diseases. N Engl J Med. 1997;336(15):1066–1071. [DOI] [PubMed] [Google Scholar]
19. Emanuelli B, Peraldi P, Filloux C, Chavey C, Freidinger K, Hilton DJ, Hotamisligil GS, Van Obberghen E. SOCS-3 inhibits insulin signaling and is up-regulated in response to tumor necrosis factor-alpha in the adipose tissue of obese mice. J Biol Chem. 2001;276(51):47944–47949. [DOI] [PubMed] [Google Scholar]
20. Krebs DL, Hilton DJ. SOCS: physiological suppressors of cytokine signaling. J Cell Sci. 2000;113(Pt 16):2813–2819. [DOI] [PubMed] [Google Scholar]
21. Rui L, Yuan M, Frantz D, Shoelson S, White MF. SOCS-1 and SOCS-3 block insulin signaling by ubiquitin-mediated degradation of IRS1 and IRS2. J Biol Chem. 2002;277(44):42394–42398. [DOI] [PubMed] [Google Scholar]
22. Zierath JR, He L, Gumà A, Odegoard Wahlström E, Klip A, Wallberg-Henriksson H. Insulin action on glucose transport and plasma membrane GLUT4 content in skeletal muscle from patients with NIDDM. Diabetologia. 1996;39(10):1180–1189. [DOI] [PubMed] [Google Scholar]
23. Liu R, Zhang C, Shi Y, Zhang F, Li L, Wang X, Ling Y, Fu H, Dong W, Shen J, Reeves A, Greenberg AS, Zhao L, Peng Y, Ding X. Dysbiosis of gut microbiota associated with clinical parameters in polycystic ovary syndrome. Front Microbiol. 2017;8(324):324. [DOI] [PMC free article] [PubMed] [Google Scholar]
24. Zhu Q, Zhou H, Zhang A, Gao R, Yang S, Zhao C, Wang Y, Hu J, Goswami R, Gong L, Li Q. Serum LBP is associated with insulin resistance in women with PCOS. PLoS One. 2016;11(1):e0145337. [DOI] [PMC free article] [PubMed] [Google Scholar]
25. Modan M, Harris MI, Halkin H. Evaluation of WHO and NDDG criteria for impaired glucose tolerance. Results from two national samples. Diabetes. 1989;38(12):1630–1635. [DOI] [PubMed] [Google Scholar]
26. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;106(25):3143–3421. [PubMed] [Google Scholar]
27. González F, Kirwan JP, Rote NS, Minium J. Glucose ingestion stimulates atherothrombotic inflammation in polycystic ovary syndrome. Am J Physiol Endocrinol Metab. 2013;304(4):E375–E383. [DOI] [PMC free article] [PubMed] [Google Scholar]
28. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22(9):1462–1470. [DOI] [PubMed] [Google Scholar]
29. Yeh ST. Using a trapezoidal rule for the area under a curve calculation – SAS advanced tutorial. In: Proceedings of the 27th Annual Conference of SAS Users Group International. 14–17 April 2002; Orlando, FL. Abstract 229. [Google Scholar]
30. González F, Minium J, Rote NS, Kirwan JP. Hyperglycemia alters tumor necrosis factor-α release from mononuclear cells in women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2005;90(9):5336–5342. [DOI] [PubMed] [Google Scholar]
31. Carmina E, Bucchieri S, Esposito A, Del Puente A, Mansueto P, Orio F, Di Fede G, Rini G. Abdominal fat quantity and distribution in women with polycystic ovary syndrome and extent of its relation to insulin resistance. J Clin Endocrinol Metab. 2007;92(7):2500–2505. [DOI] [PubMed] [Google Scholar]
32. Bell LN, Cai L, Johnstone BH, Traktuev DO, March KL, Considine RV. A central role for hepatocyte growth factor in adipose tissue angiogenesis. Am J Physiol Endocrinol Metab. 2008;294(2):E336–E344. [DOI] [PubMed] [Google Scholar]
33. Aljada A, Ghanim H, Dandona P. Translocation of p47phox and activation of NADPH oxidase in mononuclear cells. Methods Mol Biol. 2002;196:99–103. [DOI] [PubMed] [Google Scholar]
34. Legro RS, Schlaff WD, Diamond MP, Coutifaris C, Casson PR, Brzyski RG, Christman GM, Trussell JC, Krawetz SA, Snyder PJ, Ohl D, Carson SA, Steinkampf MP, Carr BR, McGovern PG, Cataldo NA, Gosman GG, Nestler JE, Myers ER, Santoro N, Eisenberg E, Zhang M, Zhang H; Reproductive Medicine Network . Total testosterone assays in women with polycystic ovary syndrome: precision and correlation with hirsutism. J Clin Endocrinol Metab. 2010;95(12):5305–5313. [DOI] [PMC free article] [PubMed] [Google Scholar]
35. González F, Considine RV, Abdelhadi OA, Acton AJ. Data from: Saturated fat ingestion promotes lipopolysaccharide-mediated inflammation and insulin resistance in polycystic ovary syndrome. figshare 2018. Deposited 24 October 2018. 10.6084/m9.figshare.7246082. [DOI] [PMC free article] [PubMed]
36. González F, Nair KS, Daniels JK, Basal E, Schimke JM. Hyperandrogenism sensitizes mononuclear cells to promote glucose-induced inflammation in lean reproductive-age women. Am J Physiol Endocrinol Metab. 2012;302(3):E297–E306. [DOI] [PMC free article] [PubMed] [Google Scholar]
37. Dandona P, Ghanim H, Chaudhuri A, Dhindsa S, Kim SS. Macronutrient intake induces oxidative and inflammatory stress: potential relevance to atherosclerosis and insulin resistance. Exp Mol Med. 2010;42(4):245–253. [DOI] [PMC free article] [PubMed] [Google Scholar]
38. Feinstein R, Kanety H, Papa MZ, Lunenfeld B, Karasik A. Tumor necrosis factor-α suppresses insulin-induced tyrosine phosphorylation of insulin receptor and its substrates. J Biol Chem. 1993;268(35):26055–26058. [PubMed] [Google Scholar]
39. Hotamisligil GS, Murray DL, Choy LN, Spiegelman BM. Tumor necrosis factor α inhibits signaling from the insulin receptor. Proc Natl Acad Sci USA. 1994;91(11):4854–4858. [DOI] [PMC free article] [PubMed] [Google Scholar]
40. del Aguila LF, Claffey KP, Kirwan JP. TNF-α impairs insulin signaling and insulin stimulation of glucose uptake in C₂C₁₂ muscle cells. Am J Physiol. 1999;276(5 Pt 1):E849–E855. [DOI] [PubMed] [Google Scholar]
41. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. 2003;112(12):1796–1808. [DOI] [PMC free article] [PubMed] [Google Scholar]
42. Cinti S, Mitchell G, Barbatelli G, Murano I, Ceresi E, Faloia E, Wang S, Fortier M, Greenberg AS, Obin MS. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J Lipid Res. 2005;46(11):2347–2355. [DOI] [PubMed] [Google Scholar]
43. Fain JN, Bahouth SW, Madan AK. TNFα release by the nonfat cells of human adipose tissue. Int J Obes Relat Metab Disord. 2004;28(4):616–622. [DOI] [PubMed] [Google Scholar]
44. Brewer HB., Jr Hypertriglyceridemia: changes in the plasma lipoproteins associated with an increased risk of cardiovascular disease. Am J Cardiol. 1999;83(9B):3F–12F. [DOI] [PubMed] [Google Scholar]
45. Khovidhunkit W, Kim MS, Memon RA, Shigenaga JK, Moser AH, Feingold KR, Grunfeld C. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host. J Lipid Res. 2004;45(7):1169–1196. [DOI] [PubMed] [Google Scholar]
46. Feingold KR, Hardardottir I, Memon R, Krul EJ, Moser AH, Taylor JM, Grunfeld C. Effect of endotoxin on cholesterol biosynthesis and distribution in serum lipoproteins in Syrian hamsters. J Lipid Res. 1993;34(12):2147–2158. [PubMed] [Google Scholar]
47. González F, Rote NS, Minium J, Kirwan JP. In vitro evidence that hyperglycemia stimulates tumor necrosis factor-α release in obese women with polycystic ovary syndrome. J Endocrinol. 2006;188(3):521–529. [DOI] [PubMed] [Google Scholar]
48. Thornton K, Asemota O, Jindal S, Charron M, Buyuk E. High fat diet and aging are associated with macrophage infiltration in mice ovaries. In: Program of the 71st meeting of the American Society for Reproductive Medicine. 17–21 October 2015; Baltimore, MD. Abstract O-273. [Google Scholar]
49. Zhang LH, Rodriguez H, Ohno S, Miller WL. Serine phosphorylation of human P450c17 increases 17,20-lyase activity: implications for adrenarche and the polycystic ovary syndrome. Proc Natl Acad Sci USA. 1995;92(23):10619–10623. [DOI] [PMC free article] [PubMed] [Google Scholar]
50. Spaczynski RZ, Arici A, Duleba AJ. Tumor necrosis factor-alpha stimulates proliferation of rat ovarian theca-interstitial cells. Biol Reprod. 1999;61(4):993–998. [DOI] [PubMed] [Google Scholar]
51. González F, Mather KJ, Considine RV, Pardue SL, Acton AJ. Suppression of nutrient-induced inflammation with a nonsteroidal anti-inflammatory agent ameliorates ovarian dysfunction in lean insulin-sensitive women with polycystic ovary syndrome. In: Program of the 71st meeting of the American Society for Reproductive Medicine. 17–21 October 2015; Baltimore, MD. Abstract O-51. [Google Scholar]

[B1] 1. González F, Rote NS, Minium J, Kirwan JP. Reactive oxygen species-induced oxidative stress in the development of insulin resistance and hyperandrogenism in polycystic ovary syndrome. J Clin Endocrinol Metab. 2006;91(1):336–340. [DOI] [PubMed] [Google Scholar]

[B2] 2. González F, Sia CL, Shepard MK, Rote NS, Minium J. Hyperglycemia-induced oxidative stress is independent of excess abdominal adiposity in normal-weight women with polycystic ovary syndrome. Hum Reprod. 2012;27(12):3560–3568. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B3] 3. González F, Rote NS, Minium J, Kirwan JP. Increased activation of nuclear factor kappaB triggers inflammation and insulin resistance in polycystic ovary syndrome. J Clin Endocrinol Metab. 2006;91(4):1508–1512. [DOI] [PubMed] [Google Scholar]

[B4] 4. González F, Sia CL, Shepard MK, Rote NS, Minium J. Inflammation in response to glucose ingestion is independent of excess abdominal adiposity in normal-weight women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2012;97(11):4071–4079. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B5] 5. González F, Sia CL, Shepard MK, Rote NS, Minium J. The altered mononuclear cell-derived cytokine response to glucose ingestion is not regulated by excess adiposity in polycystic ovary syndrome. J Clin Endocrinol Metab. 2014;99(11):E2244–E2251. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B6] 6. Dunaif A, Segal KR, Futterweit W, Dobrjansky A. Profound peripheral insulin resistance, independent of obesity, in polycystic ovary syndrome. Diabetes. 1989;38(9):1165–1174. [DOI] [PubMed] [Google Scholar]

[B7] 7. Corbould A, Kim YB, Youngren JF, Pender C, Kahn BB, Lee A, Dunaif A. Insulin resistance in the skeletal muscle of women with PCOS involves intrinsic and acquired defects in insulin signaling. Am J Physiol Endocrinol Metab. 2005;288(5):E1047–E1054. [DOI] [PubMed] [Google Scholar]

[B8] 8. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–1023. [DOI] [PubMed] [Google Scholar]

[B9] 9. Schwiertz A, Taras D, Schäfer K, Beijer S, Bos NA, Donus C, Hardt PD. Microbiota and SCFA in lean and overweight healthy subjects. Obesity (Silver Spring). 2010;18(1):190–195. [DOI] [PubMed] [Google Scholar]

[B10] 10. Bäckhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, Semenkovich CF, Gordon JI. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci USA. 2004;101(44):15718–15723. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B11] 11. Fava F, Gitau R, Griffin BA, Gibson GR, Tuohy KM, Lovegrove JA. The type and quantity of dietary fat and carbohydrate alter faecal microbiome and short-chain fatty acid excretion in a metabolic syndrome ‘at-risk’ population. Int J Obes. 2013;37(2):216–223. [DOI] [PubMed] [Google Scholar]

[B12] 12. Deopurkar R, Ghanim H, Friedman J, Abuaysheh S, Sia CL, Mohanty P, Viswanathan P, Chaudhuri A, Dandona P. Differential effects of cream, glucose, and orange juice on inflammation, endotoxin, and the expression of Toll-like receptor-4 and suppressor of cytokine signaling-3. Diabetes Care. 2010;33(5):991–997. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B13] 13. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM, Burcelin R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes. 2008;57(6):1470–1481. [DOI] [PubMed] [Google Scholar]

[B14] 14. Lassenius MI, Pietiläinen KH, Kaartinen K, Pussinen PJ, Syrjänen J, Forsblom C, Pörsti I, Rissanen A, Kaprio J, Mustonen J, Groop PH, Lehto M; FinnDiane Study Group . Bacterial endotoxin activity in human serum is associated with dyslipidemia, insulin resistance, obesity, and chronic inflammation. Diabetes Care. 2011;34(8):1809–1815. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B15] 15. Xu XH, Shah PK, Faure E, Equils O, Thomas L, Fishbein MC, Luthringer D, Xu XP, Rajavashisth TB, Yano J, Kaul S, Arditi M. Toll-like receptor-4 is expressed by macrophages in murine and human lipid-rich atherosclerotic plaques and upregulated by oxidized LDL. Circulation. 2001;104(25):3103–3108. [DOI] [PubMed] [Google Scholar]

[B16] 16. Gutsmann T, Müller M, Carroll SF, MacKenzie RC, Wiese A, Seydel U. Dual role of lipopolysaccharide (LPS)-binding protein in neutralization of LPS and enhancement of LPS-induced activation of mononuclear cells. Infect Immun. 2001;69(11):6942–6950. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B17] 17. Covert MW, Leung TH, Gaston JE, Baltimore D. Achieving stability of lipopolysaccharide-induced NF-kappaB activation. Science. 2005;309(5742):1854–1857. [DOI] [PubMed] [Google Scholar]

[B18] 18. Barnes PJ, Karin M. Nuclear factor-kappaB: a pivotal transcription factor in chronic inflammatory diseases. N Engl J Med. 1997;336(15):1066–1071. [DOI] [PubMed] [Google Scholar]

[B19] 19. Emanuelli B, Peraldi P, Filloux C, Chavey C, Freidinger K, Hilton DJ, Hotamisligil GS, Van Obberghen E. SOCS-3 inhibits insulin signaling and is up-regulated in response to tumor necrosis factor-alpha in the adipose tissue of obese mice. J Biol Chem. 2001;276(51):47944–47949. [DOI] [PubMed] [Google Scholar]

[B20] 20. Krebs DL, Hilton DJ. SOCS: physiological suppressors of cytokine signaling. J Cell Sci. 2000;113(Pt 16):2813–2819. [DOI] [PubMed] [Google Scholar]

[B21] 21. Rui L, Yuan M, Frantz D, Shoelson S, White MF. SOCS-1 and SOCS-3 block insulin signaling by ubiquitin-mediated degradation of IRS1 and IRS2. J Biol Chem. 2002;277(44):42394–42398. [DOI] [PubMed] [Google Scholar]

[B22] 22. Zierath JR, He L, Gumà A, Odegoard Wahlström E, Klip A, Wallberg-Henriksson H. Insulin action on glucose transport and plasma membrane GLUT4 content in skeletal muscle from patients with NIDDM. Diabetologia. 1996;39(10):1180–1189. [DOI] [PubMed] [Google Scholar]

[B23] 23. Liu R, Zhang C, Shi Y, Zhang F, Li L, Wang X, Ling Y, Fu H, Dong W, Shen J, Reeves A, Greenberg AS, Zhao L, Peng Y, Ding X. Dysbiosis of gut microbiota associated with clinical parameters in polycystic ovary syndrome. Front Microbiol. 2017;8(324):324. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B24] 24. Zhu Q, Zhou H, Zhang A, Gao R, Yang S, Zhao C, Wang Y, Hu J, Goswami R, Gong L, Li Q. Serum LBP is associated with insulin resistance in women with PCOS. PLoS One. 2016;11(1):e0145337. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B25] 25. Modan M, Harris MI, Halkin H. Evaluation of WHO and NDDG criteria for impaired glucose tolerance. Results from two national samples. Diabetes. 1989;38(12):1630–1635. [DOI] [PubMed] [Google Scholar]

[B26] 26. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;106(25):3143–3421. [PubMed] [Google Scholar]

[B27] 27. González F, Kirwan JP, Rote NS, Minium J. Glucose ingestion stimulates atherothrombotic inflammation in polycystic ovary syndrome. Am J Physiol Endocrinol Metab. 2013;304(4):E375–E383. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B28] 28. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22(9):1462–1470. [DOI] [PubMed] [Google Scholar]

[B29] 29. Yeh ST. Using a trapezoidal rule for the area under a curve calculation – SAS advanced tutorial. In: Proceedings of the 27th Annual Conference of SAS Users Group International. 14–17 April 2002; Orlando, FL. Abstract 229. [Google Scholar]

[B30] 30. González F, Minium J, Rote NS, Kirwan JP. Hyperglycemia alters tumor necrosis factor-α release from mononuclear cells in women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2005;90(9):5336–5342. [DOI] [PubMed] [Google Scholar]

[B31] 31. Carmina E, Bucchieri S, Esposito A, Del Puente A, Mansueto P, Orio F, Di Fede G, Rini G. Abdominal fat quantity and distribution in women with polycystic ovary syndrome and extent of its relation to insulin resistance. J Clin Endocrinol Metab. 2007;92(7):2500–2505. [DOI] [PubMed] [Google Scholar]

[B32] 32. Bell LN, Cai L, Johnstone BH, Traktuev DO, March KL, Considine RV. A central role for hepatocyte growth factor in adipose tissue angiogenesis. Am J Physiol Endocrinol Metab. 2008;294(2):E336–E344. [DOI] [PubMed] [Google Scholar]

[B33] 33. Aljada A, Ghanim H, Dandona P. Translocation of p47phox and activation of NADPH oxidase in mononuclear cells. Methods Mol Biol. 2002;196:99–103. [DOI] [PubMed] [Google Scholar]

[B34] 34. Legro RS, Schlaff WD, Diamond MP, Coutifaris C, Casson PR, Brzyski RG, Christman GM, Trussell JC, Krawetz SA, Snyder PJ, Ohl D, Carson SA, Steinkampf MP, Carr BR, McGovern PG, Cataldo NA, Gosman GG, Nestler JE, Myers ER, Santoro N, Eisenberg E, Zhang M, Zhang H; Reproductive Medicine Network . Total testosterone assays in women with polycystic ovary syndrome: precision and correlation with hirsutism. J Clin Endocrinol Metab. 2010;95(12):5305–5313. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B35] 35. González F, Considine RV, Abdelhadi OA, Acton AJ. Data from: Saturated fat ingestion promotes lipopolysaccharide-mediated inflammation and insulin resistance in polycystic ovary syndrome. figshare 2018. Deposited 24 October 2018. 10.6084/m9.figshare.7246082. [DOI] [PMC free article] [PubMed]

[B36] 36. González F, Nair KS, Daniels JK, Basal E, Schimke JM. Hyperandrogenism sensitizes mononuclear cells to promote glucose-induced inflammation in lean reproductive-age women. Am J Physiol Endocrinol Metab. 2012;302(3):E297–E306. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B37] 37. Dandona P, Ghanim H, Chaudhuri A, Dhindsa S, Kim SS. Macronutrient intake induces oxidative and inflammatory stress: potential relevance to atherosclerosis and insulin resistance. Exp Mol Med. 2010;42(4):245–253. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B38] 38. Feinstein R, Kanety H, Papa MZ, Lunenfeld B, Karasik A. Tumor necrosis factor-α suppresses insulin-induced tyrosine phosphorylation of insulin receptor and its substrates. J Biol Chem. 1993;268(35):26055–26058. [PubMed] [Google Scholar]

[B39] 39. Hotamisligil GS, Murray DL, Choy LN, Spiegelman BM. Tumor necrosis factor α inhibits signaling from the insulin receptor. Proc Natl Acad Sci USA. 1994;91(11):4854–4858. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B40] 40. del Aguila LF, Claffey KP, Kirwan JP. TNF-α impairs insulin signaling and insulin stimulation of glucose uptake in C₂C₁₂ muscle cells. Am J Physiol. 1999;276(5 Pt 1):E849–E855. [DOI] [PubMed] [Google Scholar]

[B41] 41. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. 2003;112(12):1796–1808. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B42] 42. Cinti S, Mitchell G, Barbatelli G, Murano I, Ceresi E, Faloia E, Wang S, Fortier M, Greenberg AS, Obin MS. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J Lipid Res. 2005;46(11):2347–2355. [DOI] [PubMed] [Google Scholar]

[B43] 43. Fain JN, Bahouth SW, Madan AK. TNFα release by the nonfat cells of human adipose tissue. Int J Obes Relat Metab Disord. 2004;28(4):616–622. [DOI] [PubMed] [Google Scholar]

[B44] 44. Brewer HB., Jr Hypertriglyceridemia: changes in the plasma lipoproteins associated with an increased risk of cardiovascular disease. Am J Cardiol. 1999;83(9B):3F–12F. [DOI] [PubMed] [Google Scholar]

[B45] 45. Khovidhunkit W, Kim MS, Memon RA, Shigenaga JK, Moser AH, Feingold KR, Grunfeld C. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host. J Lipid Res. 2004;45(7):1169–1196. [DOI] [PubMed] [Google Scholar]

[B46] 46. Feingold KR, Hardardottir I, Memon R, Krul EJ, Moser AH, Taylor JM, Grunfeld C. Effect of endotoxin on cholesterol biosynthesis and distribution in serum lipoproteins in Syrian hamsters. J Lipid Res. 1993;34(12):2147–2158. [PubMed] [Google Scholar]

[B47] 47. González F, Rote NS, Minium J, Kirwan JP. In vitro evidence that hyperglycemia stimulates tumor necrosis factor-α release in obese women with polycystic ovary syndrome. J Endocrinol. 2006;188(3):521–529. [DOI] [PubMed] [Google Scholar]

[B48] 48. Thornton K, Asemota O, Jindal S, Charron M, Buyuk E. High fat diet and aging are associated with macrophage infiltration in mice ovaries. In: Program of the 71st meeting of the American Society for Reproductive Medicine. 17–21 October 2015; Baltimore, MD. Abstract O-273. [Google Scholar]

[B49] 49. Zhang LH, Rodriguez H, Ohno S, Miller WL. Serine phosphorylation of human P450c17 increases 17,20-lyase activity: implications for adrenarche and the polycystic ovary syndrome. Proc Natl Acad Sci USA. 1995;92(23):10619–10623. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B50] 50. Spaczynski RZ, Arici A, Duleba AJ. Tumor necrosis factor-alpha stimulates proliferation of rat ovarian theca-interstitial cells. Biol Reprod. 1999;61(4):993–998. [DOI] [PubMed] [Google Scholar]

[B51] 51. González F, Mather KJ, Considine RV, Pardue SL, Acton AJ. Suppression of nutrient-induced inflammation with a nonsteroidal anti-inflammatory agent ameliorates ovarian dysfunction in lean insulin-sensitive women with polycystic ovary syndrome. In: Program of the 71st meeting of the American Society for Reproductive Medicine. 17–21 October 2015; Baltimore, MD. Abstract O-51. [Google Scholar]

PERMALINK

Saturated Fat Ingestion Promotes Lipopolysaccharide-Mediated Inflammation and Insulin Resistance in Polycystic Ovary Syndrome

Frank González

Robert V Considine

Ola A Abdelhadi

Anthony J Acton

Abstract

Context

Objective

Design

Setting

Patients

Main Outcome Measures

Results

Conclusion

Materials and Methods

Participants

Study design

Cream challenge test

Oral glucose tolerance test

HCG stimulation test

Body composition assessment

Real-time PCR

Western blotting

Plasma and serum measurements

Statistics

Results

Age, body composition, and blood pressure

Table 1.

Plasma LPS and TLR-4 mRNA and protein content

Figure 1.

Figure 2.

Plasma TNFα and SOCS-3 mRNA and protein content

Figure 3.

Insulin sensitivity and fasting lipids

Basal hormone levels and HCG-stimulated androgen and 17-OHP responses

Correlations

Table 2.

Table 3.

Discussion

Acknowledgments

Glossary

Abbreviations:

References

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases