Non-linear association between testosterone and LDL concentrations in men

The impact of sex hormones on metabolic syndrome: univariable and multivariable Mendelian randomization studies

BACKGROUND

Observational studies have found associations between sex hormones and metabolic syndrome(Mets), but the causal relationships remains unclear. This study utilizes univariable and multivariable Mendelian randomization (MR) to elucidate the associations between sex hormones (including sex hormone-binding globulin(SHBG), estradiol(E2), testosterone(T)) and Mets and its subtypes (including waist circumference(WC), fasting blood glucose(FBG), high blood pressure(HBP), high-density lipoprotein(HDL-C), triglycerides(TG)).

METHODS

We utilized summary data from large-scale genome-wide association studies. Univariable Mendelian randomization (UMVMR) analysis was primarily conducted using the inverse variance weighted method (IVW), with secondary analyses employing the weighted median, MR-Egger regression, simple mode method, and weighted mode method. Subsequently, multivariable Mendelian randomization (MVMR) was employed to assess the causal relationships between SHBG, T, E2, and MetS and its components: WC, FPG, HBP, HDL-C, and TG. Sensitivity analyses were conducted to assess result reliability.

RESULTS

Genetically predicted SHBG was significantly negatively associated with MetS (UMVMR: β=-0.72; 95% CI = 0.41 to 0.57; P = 1.28e-17; MVMR: β=-0.60; 95% CI=-0.83 to -0.38; P < 0.001). Positive causal relationships were observed between SHBG and WC(MVMR: β = 0.10; 95% CI = 0.03 to 0.17; P = 0.01) and HDL-C (MVMR: β = 0.41; 95% CI = 0.21 to 0.60; P < 0.001), while negative causal relationships were found between SHBG and HBP (MVMR: β=-0.02; 95% CI=-0.04 to -0.00; P = 0.02), TG (MVMR: β=-0.48; 95% CI=-0.70 to -0.26; P < 0.001). Genetically predicted E2 exhibited a negative association with TG (MVMR: β=-1.49; 95% CI=-2.48 to -0.50; P = 0.003). Genetically predicted T was negatively associated with TG (MVMR: β=-0.36; 95% CI=-0.71 to -0.00; P = 0.049) and WC (MVMR: β=-0.13; 95% CI=-0.24 to -0.02; P = 0.02), with inconsistent sensitivity analyses. Additionally, No other causal associations were found.

CONCLUSION

Our study indicates that SHBG is a protective factor for MetS, potentially delaying its onset and progression through improvements in HBP and TG. Furthermore, T and E2 may improve TG levels, with T also reducing WC levels. Importantly, our study provides new insights for the prevention and treatment of MetS.

Lipoprotein alterations in endocrine disorders - a review of the recent developments in the field

Dyslipidemia is one of the most common disorders worldwide, which, if left untreated, results in a multitude of complications. Thus proper diagnostics, which includes identifying of secondary causes of dyslipidemia is crucial. Endocrine disorders are an important cause of secondary dyslipidemia. This paper aims to review the publications on lipoprotein alterations in endocrine disorders from the past two years and provide an overview of the recent discoveries in this dynamically developing and large field. Significant changes in lipoprotein serum concentrations are present in most endocrinological diseases and can be modified with proper treatment. Some lipoproteins have also been proposed as markers in some endocrine diseases, e.g., thyroid carcinoma. From the scope of endocrine disorders, the largest number of studies explored the lipoprotein changes in polycystic ovary syndrome and in women during the menopausal and peri-menopausal period. Even though the association of thyroid disorders with dyslipidemia is already well studied, new research has delivered some exciting findings about lipoprotein alterations in euthyroid patients with either positive antithyroid peroxidase antibodies or reduced sensitivity to thyroid hormones. The problem of the adverse metabolic profile, including dyslipidemia in hypoprolactinemia has been recognized. Moreover, this review describes other significant discoveries encompassing lipoprotein alterations in disorders of the adrenals, thyroid, parathyroid glands, pituitary, and gonads. The up-to-date knowledge of the influence of endocrine disorders and hormonal changes on serum lipoproteins is prudent as it can significantly impact therapeutic decisions.

Analysis of the association between testosterone and cardiovascular disease potential risk factor apolipoprotein B in adult males without cancer: national health and nutrition examination survey 2011-2016

Background

Over the years, there has been extensive exploration of the association between testosterone and lipid profiles, yet the precise mechanisms underlying their interaction remain incompletely elucidated. Similarly, there is a dearth of research on the correlation between serum apolipoprotein B (apoB) and serum total testosterone (TT), particularly within specific populations.

Methods

We conducted a cross-sectional study to assess the relationship between serum TT concentration and serum apoB concentration. Using the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016, we employed weighted generalized linear models, weighted univariate, weighted multivariate analysis, and smooth curve fitting to assist in exploring the relationship between serum TT and apoB. Serum apoB concentration served as the independent variable, and serum TT concentration as the dependent variable. ApoB was divided into four quartiles-Q1 (<0.7g/L, N=691), Q2 (≥0.7g/L to <0.9g/L, N=710), Q3 (≥0.9g/L to <1.1g/L, N=696), and Q4 (≥1.1g/L, N=708)-thereby further solidifying the stable association between the two. Additionally, the application of smooth curve fitting will contribute to a more detailed elucidation of the specific relationship between serum TT concentration and serum apoB concentration under different factors (Drinking, Smoke, Diabetes, Hypertension, and High cholesterol level.).

Results

The results indicate a negative correlation between serum TT concentration and apoB concentration (β=-113.4; 95% CI: -146.6, -80.2; P<0.001). After adjusting for confounding variables, the negative correlation between apoB concentration and TT concentration remains significant (β=-61.0; 95% CI: -116.7, -5.2; P=0.040). When apoB concentration was converted from a continuous variable to a categorical variable (quartiles: Q1<0.7g/L; Q2:≥0.7g/L to<0.9g/L; Q3:≥0.9g/L to <1.1g/L; Q4: ≥1.1g/L), TT level of participants in the highest quartile (≥1.1g/L) was -47.2 pg/mL (95% CI: -91.2, -3.3; P=0.045) lower than that in the lowest quartile (<0.7g/L). The smooth curve fitting diagram revealed differences in the relationship between TT concentration and apoB among individuals with different cardiovascular disease (CVD) risk factors.

Conclusions

This study elucidates a robust inverse correlation between serum TT concentration and apoB concentration, maintaining statistical significance even upon adjustment for confounding factors. These findings present a promising avenue for addressing the prevention and treatment of low testosterone and CVD.