Associations of plasma hypocretin-1 with metabolic and reproductive health: Two systematic reviews of clinical studies

Variability in Sleep Duration and Biomarkers of Cardiovascular Disease Across the Menstrual Cycle

Variability in sleep duration and cardiovascular health have been infrequently investigated, particularly among reproductive-age women. We examined these associations across the menstrual cycle among a cohort of 250 healthy premenopausal women, aged 18-44 years. The BioCycle study (New York, 2005-2007) collected cardiovascular biomarkers (serum high- and low-density lipoprotein (HDL, LDL), total cholesterol, triglycerides, and C-reactive protein (CRP)) at key time points along the menstrual cycle (follicular, ovulatory, and luteal phases). Women also recorded sleep duration in daily diaries. From these data, we computed L-moments, robust versions of location, dispersion, skewness, and kurtosis. We fitted linear mixed models with random intercepts and inverse probability weighting to estimate associations between sleep variability and cardiovascular biomarkers, accounting for demographic, lifestyle, health, and reproductive factors. Sleep dispersion (any deviation from mean duration) was associated with lower mean LDL for nonshift workers and non-White women. Skewed sleep duration was associated with higher mean CRP and lower mean total cholesterol. Sleep durations with extreme short and long bouts (kurtosis) were associated with a lower mean HDL, but not mean CRP, LDL, or triglycerides. Sleep duration modified associations between sleep dispersion and LDL, HDL, and total cholesterol. Even in young and healthy women, sleep duration variability could influence cardiovascular health.

Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis

Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.