Using metabolic markers to identify insulin resistance in premenopausal women with and without polycystic ovary syndrome

[Analysis of Risk Factors for Recurrent Pregnancy Loss in Patients Undergoing in vitro Fertilization-Embryo Transfer]

Objective

Recurrent pregnancy loss (RPL) presents a formidable challenge for individuals undergoing in vitro fertilization-embryo transfer (IVF-ET), forming both a clinical dilemma and a focal point for scientific inquiry. This study endeavors to investigate the intricate interplay between clinical features, such as age, body mass index (BMI), and waist-to-hip ratio (WHR), and routine laboratory parameters, including sex hormones, blood composition, liver and thyroid functions, thyroid antibodies, and coagulation indicators, in RPL patients undergoing IVF-ET. By meticulously analyzing these variables, we aim to uncover the latent risk factors predisposing individuals to RPL. Identifying potential factors such as advanced maternal age, obesity, and insulin resistance will provide clinicians with vital insights and empirical evidence to strengthen preventive strategies aimed at reducing miscarriage recurrence.

Methods

This retrospective case-controlled study included RPL patients who underwent IVF-ET treatment at Sun Yat-sen Memorial Hospital, Sun Yat-sen University, between January 2012 and March 2021 as the case cohort, compared with women receiving assisted reproductive treatment due to male infertility as the control cohort. The fasting peripheral blood was collected 5 days before the first menstrual cycle at least 12 weeks after the last abortion. The clinical characteristics and relevant laboratory indexes of the two groups were compared. Employing both univariate and multivariate logistic regression analyses, we sought to unearth potential high-risk factors underlying RPL. Additionally, a linear trend analysis was conducted to assess the linear relationship between total testosterone (TT) levels and the number of miscarriages.

Results

In contrast to the control cohort, the RPL cohort exhibited significant increases in age, BMI, and WHR (P<0.05). Notably, TT levels were markedly lower in the RPL cohort (P=0.022), while no significant differences were observed between the two groups concerning basal follicle-stimulating hormone, luteinizing hormone, estradiol, progesterone, prolactin levels, and anti-Müllerian hormone levels (P>0.05). Moreover, fasting insulin (FINS) levels and HOMA-IR index were notably elevated in the RPL cohort relative to the control cohort (P<0.001), although no significant differences were observed in fasting blood glucose levels (P>0.05). Furthermore, the neutrophil (NEU) count and NEU-to-lymphocyte ratio were notably higher in the RPL cohort (P<0.01). Univariate logistic regression analysis identified several factors, including age≥35 years old, BMI≥25 kg/m2, WHR>0.8, FINS>10 mU/L, HOMA-IR>2.14, NEU count>6.3×109 L－1, and an elevated NEU/lymphocyte ratio (NLR), as significantly increasing the risk of RPL (P<0.05). Although TT levels were within the normal range for both cohorts, higher TT levels were associated with a diminished RPL risk (odds ratio [OR]=0.67, 95% confidence interval [CI]: 0.510-0.890, P=0.005). After adjustments for confounding factors, age≥35 years old (OR=1.91, 95% CI: 1.06-3.43), WHR>0.8 (OR=2.30, 95% CI: 1.26-4.19), and FINS>10 mU/L (OR=4.50, 95% CI: 1.30-15.56) emerged as potent risk factors for RPL (P<0.05). Conversely, higher TT levels were associated with a reduced RPL risk (OR=0.59, 95% CI: 0.38-0.93, P=0.023). Furthermore, the linear trend analysis unveiled a discernible linear association between TT levels and the number of miscarriages (P trend=0.003), indicating a declining trend in TT levels with escalating miscarriage occurrences.

Conclusion

In patients undergoing IVF-ET, advanced maternal age, lower TT levels, increased WHR, and elevated FINS levels emerged as potent risk factors for RPL. These findings provide clinicians with valuable insights and facilitate the identification of patients who are at high risks and the formulation of preventive strategies to reduce the recurrence of miscarriages.

Non-Alcoholic Fatty Liver Disease in Patients with Polycystic Ovary Syndrome: A Systematic Review, Meta-Analysis, and Meta-Regression

BACKGROUND

The metabolic effects of polycystic ovary syndrome (PCOS) may increase the risk of non-alcoholic fatty liver disease (NAFLD). However, the burden of NAFLD in PCOS has not been unequivocally defined. This systematic review (SR), meta-analysis (MA) assessed NAFLD's prevalence, and risk factors in patients with PCOS.

METHODS

A literature search was performed in MEDLINE, Scopus, and Scielo. First, we performed a MA of proportions to estimate the prevalence of NAFLD in PCOS. Second, we performed meta-analyses of precalculated adjusted odds ratios to examine NAFLD risk factors. Finally, we performed a meta-regression to model how the estimated prevalence changed with changes in prespecified variables.

RESULTS

We identified 817 articles from the database searches. Thirty-six were included. MA of proportions found a pooled NAFLD prevalence of 43% (95% CI, 35-52%) with high heterogeneity (I² = 97.2%). BMI, waist circumference, ALT values, HOMA-IR values, free androgen index levels, hyperandrogenism, and triglycerides were associated with significantly higher risk-adjusted odds of NAFLD among patients with PCOS. Meta-regression showed that rises in NAFLD prevalence were mediated through increases in metabolic syndrome prevalence and higher levels of HOMA-IR, free androgen index, and total testosterone.

CONCLUSION

The prevalence of NAFLD (43%) among PCOS patients is high despite their average young age, with several metabolic and PCOS-specific factors influencing its occurrence. Screening programs may aid in detecting metabolic-associated fatty liver disease and prevent its consequences. Further work is required to establish the burden of liver-related outcomes once NAFLD has progressed in the PCOS population.

Leukocyte telomere length in women with and without polycystic ovary syndrome: a systematic review and meta-analysis

AIM

To study the telomere length and the telomerase activity in women with and without polycystic ovary syndrome (PCOS).

METHODS

Relevant studies were searched from PubMed, Embase, and LILACS online databases and manual screening. The mean differences (MDs) or standardized MDs (SMDs) with their 95% confidence intervals (CIs) were calculated. The methodological quality of included studies was evaluated with the Newcastle-Ottawa Scale (NOS), and heterogeneity with the I² and Tau² statistics.

RESULTS

Six studies including 2109 non-pregnant women with (n = 1155) or without (n = 954) PCOS assessed leukocyte telomere length. There was a non-significant leukocyte telomere length difference (SMD = 0.25, 95% CI: -0.01, 0.51, p = .06, I² = 81%, Tau² = 0.08) comparing PCOS patients with the control group. Studied PCOS women were younger (MD = -1.39, 95% CI: -2.47, -0.31 years, I² = 83%), and had higher body mass index (BMI; MD = 3.66, 95% CI: 2.11, 5.20 kg/m², I² = 94%). There were significantly higher testosterone (SMD = 0.88, 95% CI: 0.65, 1.10) and luteinizing hormone levels (SMD = 0.60, 95% CI: 0.12, 1.08) in women with PCOS as compared to controls. There was a low risk of bias and there were not sufficient studies to meta-analyze other cell types.

CONCLUSIONS

Leukocyte telomere length did not differ between women with and without PCOS. Further studies with large sample sizes and including other outcomes are warranted to further substantiate the reported evidence.

Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study

BACKGROUND

Visceral adiposity plays a key role in the development of insulin resistance (IR), so surrogate index that can indicate visceral obesity may have higher predictive value for IR. This study aimed to establish and validate a new predictive model including indicator of visceral obesity for IR.

METHODS

The study population consisted of two cohorts. The derivation cohort was a group of 667 patients with newly diagnosed type 2 diabetes and the population undergoing a routine health checkup was the validation cohort. The predictive model was established by the logistic regression analysis. Its value for predicting IR was compared with other surrogate indices by the receiver operating characteristic curve.

RESULTS

The odds ratio (OR) of age, visceral fat area (VFA), triglyceride (TG), fasting plasma glucose (FPG), and alanine aminotransferase (ALT) for IR was 1.028 (95% CI, 1.008-1.048) (P < 0.01), 1.016 (95% CI, 1.009-1.023) (P < 0.001), 1.184 (95% CI, 1.005-1.396) (P < 0.05), 1.334 (95% CI, 1.225-1.451) (P < 0.001), and 1.021 (95% CI, 1.001-1.040) (P < 0.05). The formula of the predictive model was (0.0293 × age + 1.4892 × Ln VFA + 0.4966 × Ln TG + 2.784 × Ln FPG + 0.6906 × Ln ALT)/2. The area under the curve was the largest among all the previously reported predictors.

CONCLUSIONS

This study established and validated a predicting model for IR and confirmed its predictive value in comparison with other surrogate indicators, which will offer a simple and effective tool to measure IR in future large population studies.

New Insights on the Relationship between Leptin, Ghrelin, and Leptin/Ghrelin Ratio Enforced by Body Mass Index in Obesity and Diabetes

Currently, adipose tissue is considered an endocrine organ, however, there are still many questions regarding the roles of adipokines—leptin and ghrelin being two adipokines. The purpose of the study was to assess the relationship between the adipokines and their ratio with obesity and diabetes. Methods: Sixty patients (mean age 61.88 ± 10.08) were evaluated. Cardiovascular risk factors, leptin, ghrelin, and insulin resistance score values were assessed. The patients were classified according to their body mass index (BMI) as normal weight, overweight, and obese. Results: 20% normal weight, 51.7% overweight, 28.3% obese, and 23.3% diabetic. Obese patients had higher leptin values (in obese 34,360 pg/mL vs. overweight 18,000 pg/mL vs. normal weight 14,350 pg/mL, p = 0.0049) and leptin/ghrelin ratio (1055 ± 641 vs. 771.36 ± 921 vs. 370.7 ± 257, p = 0.0228). Stratifying the analyses according to the presence of obesity and patients’ gender, differences were found for leptin (p = 0.0020 in women, p = 0.0055 in men) and leptin/ghrelin ratio (p = 0.048 in women, p = 0.004 in men). Mean leptin/BMI and leptin/ghrelin/BMI ratios were significantly higher, and the ghrelin/BMI ratio was significantly lower in obese and diabetic patients. In conclusion, obesity and diabetes are associated with changes not only in the total amount but also in the level of adipokines/kg/m². Changes appear even in overweight subjects, offering a basis for early intervention in diabetic and obese patients.