Integrative network analysis highlights biological processes underlying GLP-1 stimulated insulin secretion: A DIRECT study.

Glucagon-like peptide 1 (GLP-1) stimulated insulin secretion has a considerable heritable component as estimated from twin studies, yet few genetic variants influencing this phenotype have been identified. We performed the first genome-wide association study (GWAS) of GLP-1 stimulated insulin secretion in non-diabetic individuals from the Netherlands Twin register (n = 126). This GWAS was enhanced using a tissue-specific protein-protein interaction network approach. We identified a beta-cell protein-protein interaction module that was significantly enriched for low gene scores based on the GWAS P-values and found support at the network level in an independent cohort from Tübingen, Germany (n = 100). Additionally, a polygenic risk score based on SNPs prioritized from the network was associated (P < 0.05) with glucose-stimulated insulin secretion phenotypes in up to 5,318 individuals in MAGIC cohorts. The network contains both known and novel genes in the context of insulin secretion and is enriched for members of the focal adhesion, extracellular-matrix receptor interaction, actin cytoskeleton regulation, Rap1 and PI3K-Akt signaling pathways. Adipose tissue is, like the beta-cell, one of the target tissues of GLP-1 and we thus hypothesized that similar networks might be functional in both tissues. In order to verify peripheral effects of GLP-1 stimulation, we compared the transcriptome profiling of ob/ob mice treated with liraglutide, a clinically used GLP-1 receptor agonist, versus baseline controls. Some of the upstream regulators of differentially expressed genes in the white adipose tissue of ob/ob mice were also detected in the human beta-cell network of genes associated with GLP-1 stimulated insulin secretion. The findings provide biological insight into the mechanisms through which the effects of GLP-1 may be modulated and highlight a potential role of the beta-cell expressed genes RYR2, GDI2, KIAA0232, COL4A1 and COL4A2 in GLP-1 stimulated insulin secretion.

Depression scores associate with chronotype and social jetlag in a rural population.

In public health, mood disorders are among the most important mental impairments. Patients with depressive episodes exhibit daily mood variations, abnormal patterns in sleep-wake behavior, and in the daily rhythms of several endocrine-metabolic parameters. Although the relationship between the sleep/circadian processes and mood disorders is poorly understood, clock-related therapies, such as light therapy, sleep deprivation, and rigid sleep schedules, have been shown to be effective treatments. Several studies investigated the relationship between circadian phenotype (chronotype) and depression. These focused mainly on urban populations and assessed diurnal preferences (Morningness-Eveningness score) rather than the actual timing of sleep and activity. Here, we used the Beck Depression Inventory (BDI) in an essentially rural population (N?=?4051), and investigated its relation to circadian phenotype (chronotype and social jetlag), assessed with the Munich Chronotype Questionnaire (MCTQ). In our study design, we (i) normalized both chronotype and BDI scores for age and sex (MSF(sas) and BDI(as), respectively); (ii) calculated individual social jetlag (misalignment of the biological and social time); and (iii) investigated the relationship between circadian phenotypes and BDI scores in a population homogeneous in respect to culture, socioeconomic factors, and daily light exposure. A 15.65% (N?=?634) of the participants showed mild to severe depressive BDI scores. Late chronotypes had a higher BDI(as) than intermediate and early types, which was independent of whether or not the participants were smokers. Both chronotype and BDI(as) correlated positively with social jetlag. BDI(as) was significantly higher in subjects with >2?h of social jetlag than in the rest of the population?again independent of smoking status. We also compared chronotype and social jetlag distributions between BDI categories (no symptoms, minimal symptoms, and mild to severe symptoms of depression) separately for men and women and for four age groups; specifically in the age group 31?40 yrs, subjects with mild to severe BDI scores were significantly later chronotypes and suffered from higher social jetlag. Our results indicate that misalignment of circadian and social time may be a risk factor for developing depression, especially in 31- to 40-yr-olds. These relationships should be further investigated in longitudinal studies to reveal if reduction of social jetlag should be part of prevention strategies. (Author correspondence: karla.allebrandt@med.uni-muenchen.de ).