Integrating results from genome-wide association studies (GWASs) and gene expression studies through transcriptome-wide association study (TWAS) has the potential to shed light on the causal molecular mechanisms underlying disease etiology. Here, we present a probabilistic Mendelian randomization (MR) method, PMR-Egger, for TWAS applications. PMR-Egger relies on a MR likelihood framework that unifies many existing TWAS and MR methods, accommodates multiple correlated instruments, tests the causal effect of gene on trait in the presence of horizontal pleiotropy, and is scalable to hundreds of thousands of individuals. In simulations, PMR-Egger provides calibrated type I error control for causal effect testing in the presence of horizontal pleiotropic effects, is reasonably robust under various types of model misspecifications, is more powerful than existing TWAS/MR approaches, and can directly test for horizontal pleiotropy. We illustrate the benefits of PMR-Egger in applications to 39 diseases and complex traits obtained from three GWASs including the UK Biobank.

Menopause is associated with dyslipidemia and an increased risk of cardio-cerebrovascular disease. The classic view assumes that the underlying mechanism of dyslipidemia is attributed to an insufficiency of estrogen. In addition to a decrease in estrogen, circulating follicle-stimulating hormone (FSH) levels become elevated at menopause. In this study, we find that blocking FSH reduces serum cholesterol via inhibiting hepatic cholesterol biosynthesis. First, epidemiological results show that the serum FSH levels are positively correlated with the serum total cholesterol levels, even after adjustment by considering the effects of serum estrogen. In addition, the prevalence of hypercholesterolemia is significantly higher in peri-menopausal women than that in premenopausal women. Furthermore, we generated a mouse model of FSH elevation by intraperitoneally injecting exogenous FSH into ovariectomized (OVX) mice, in which a normal level of estrogen (E2) was maintained by exogenous supplementation. Consistently, the results indicate that FSH, independent of estrogen, increases the serum cholesterol level in this mouse model. Moreover, blocking FSH signaling by anti-FSHβ antibody or ablating the FSH receptor (FSHR) gene could effectively prevent hypercholesterolemia induced by FSH injection or high-cholesterol diet feeding. Mechanistically, FSH, via binding to hepatic FSHRs, activates the Gi2α/β-arrestin-2/Akt pathway and subsequently inhibits the binding of FoxO1 with the SREBP-2 promoter, thus preventing FoxO1 from repressing SREBP-2 gene transcription. This effect, in turn, results in the upregulation of SREBP-2, which drives HMGCR nascent transcription and de novo cholesterol biosynthesis, leading to the increase of cholesterol accumulation. This study uncovers that blocking FSH signaling might be a new strategy for treating hypercholesterolemia during menopause, particularly for women in peri-menopause characterized by FSH elevation only.

Spatial panel data models are useful when longitudinal data with multiple units are available and spatial autocorrelation exists. The association found between HFMD and meteorological factors makes a contribution towards advancing knowledge with respect to the causality of HFMD and has policy implications for HFMD prevention and control.

BackgroundMacrosomia is a serious public health problem worldwide due to its increasing prevalence and adverse influences on maternal and neonatal outcomes. Maternal dyslipidemia exerts potential and adverse impacts on pregnant women and newborns. However, the association between maternal serum lipids and the risk of macrosomia has not yet been clearly elucidated. We explored the association between the maternal lipids profile at late gestation and the risk of having macrosomia among women without diabetes mellitus (DM).MethodsThe medical records of 5407 pregnant women giving birth to single live babies at term were retrospectively analyzed. Subjects with DM, hypertension, thyroid disorders and fetal malformation were excluded. Maternal fasting serum lipids were measured during late pregnancy. Logistic regression analysis was used to analyze the variables associated with the risk of macrosomia.ResultsMaternal serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels were related to macrosomia; each 1 mmol/L increase in TG resulted in a 27% increase in macrosomia risk, while each 1 mmol/L increase in HDL-C level resulted in a 37% decrease in macrosomia risk, even after adjusting for potential confounders. Notably, the risk of macrosomia increased progressively with increased maternal serum TG levels and decreased HDL-C levels. Compared with women with serum TG levels < 2.5 mmol/L, women with TG levels greater than 3.92 mmol/L had an approximately 2.8-fold increased risk of macrosomia. Compared with women with serum HDL-C levels above 2.23 mmol/L, women with HDL-C levels of less than 1.62 mmol/L had a 1.9-fold increased risk of giving birth to an infan with macrosomia. In addition, a higher risk of macrosomia was observed in women with simultaneous hypertriglyceridemia and low serum HDL-C levels (odds ratio [OR] 2.400, 95% confidence interval [CI]: 1.760–3.274) compared to those with hypertriglyceridemia or low serum HDL-C alone (OR 2.074, 95% CI: 1.609–2.673 and OR 1.363, 95% CI: 1.028–1.809, respectively).ConclusionsMaternal serum TG levels and HDL-C levels at late gestation are independent predictors of macrosomia in women without DM.Electronic supplementary materialThe online version of this article (10.1186/s12944-018-0707-7) contains supplementary material, which is available to authorized users.