Plasma Concentration of Caspase-8 Is Associated With Short Sleep Duration and the Risk of Incident Diabetes Mellitus

Very short sleep duration reveals a proteomic fingerprint that is selectively associated with incident diabetes mellitus but not with incident coronary heart disease: a cohort study

BACKGROUND

The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease.

METHODS

We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46-68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates.

RESULTS

Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06-1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD.

CONCLUSIONS

We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk

OBJECTIVE

Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk.

SUBJECTS

In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort.

RESULTS

In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy.

CONCLUSIONS

Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.

Differences in Biomarkers of Inflammation Between Novel Subgroups of Recent-Onset Diabetes

A novel clustering approach identified five subgroups of diabetes with distinct progression trajectories of complications. We hypothesized that these subgroups differ in multiple biomarkers of inflammation. Serum levels of 74 biomarkers of inflammation were measured in 414 individuals with recent adult-onset diabetes from the German Diabetes Study (GDS) allocated to five subgroups based on data-driven cluster analysis. Pairwise differences between subgroups for biomarkers were assessed with generalized linear mixed models before (model 1) and after (model 2) adjustment for the clustering variables. Participants were assigned to five subgroups: severe autoimmune diabetes (21%), severe insulin-deficient diabetes (SIDD) (3%), severe insulin-resistant diabetes (SIRD) (9%), mild obesity-related diabetes (32%), and mild age-related diabetes (35%). In model 1, 23 biomarkers showed one or more pairwise differences between subgroups (Bonferroni-corrected P < 0.0007). Biomarker levels were generally highest in SIRD and lowest in SIDD. All 23 biomarkers correlated with one or more of the clustering variables. In model 2, three biomarkers (CASP-8, EN-RAGE, IL-6) showed at least one pairwise difference between subgroups (e.g., lower CASP8, EN-RAGE, and IL-6 in SIDD vs. all other subgroups, all P < 0.0007). Thus, novel diabetes subgroups show multiple differences in biomarkers of inflammation, underlining a prominent role of inflammatory pathways in particular in SIRD.

Toxicity Induced by Cytokines, Glucose, and Lipids Increase Apoptosis and Hamper Insulin Secretion in the 1.1E7 Beta Cell-Line

Basic research on types 1 and 2 diabetes mellitus require early stage studies using beta cells or cell lines, ideally of human origin and with preserved insulin secretion in response to glucose. The 1.1E7 cells are a hybrid cell line resulting from the electrofusion of dispersed human islets and PANC-1 cells, capable of secreting insulin in response to glucose, but their survival and function under toxic conditions remains untested. This characterization is the purpose of the present study. We treated these cells with a cytokine mix, high glucose, palmitate, and the latter two combined. Under these conditions, we measured cell viability and apoptosis (MTT, Caspase Glo and TUNEL assays, as well as caspase-8 and -9 levels by Western blotting), endoplasmic reticulum stress markers (EIF2AK3, HSPA4, EIF2a, and HSPA5) by real-time PCR, and insulin secretion with a glucose challenge. All of these stimuli (i) induce apoptosis and ER stress markers expression, (ii) reduce mRNA amounts of 2–5 components of genes involved in the insulin secretory pathway, and (iii) abrogate the insulin release capability of 1.1E7 cells in response to glucose. The most pronounced effects were observed with cytokines and with palmitate and high glucose combined. This characterization may well serve as the starting point for those choosing this cell line for future basic research on certain aspects of diabetes.

A Cell's Fate: An Overview of the Molecular Biology and Genetics of Apoptosis

Apoptosis is one of the main types of regulated cell death, a complex process that can be triggered by external or internal stimuli, which activate the extrinsic or the intrinsic pathway, respectively. Among various factors involved in apoptosis, several genes and their interactive networks are crucial regulators of the outcomes of each apoptotic phase. Furthermore, mitochondria are key players in determining the way by which cells will react to internal stress stimuli, thus being the main contributor of the intrinsic pathway, in addition to providing energy for the whole process. Other factors that have been reported as important players of this intricate molecular network are miRNAs, which regulate the genes involved in the apoptotic process. Imbalance in any of these mechanisms can lead to the development of several illnesses, hence, an overall understanding of these processes is essential for the comprehension of such situations. Although apoptosis has been widely studied, the current literature lacks an updated and more general overview on this subject. Therefore, here, we review and discuss the mechanisms of apoptosis, highlighting the roles of genes, miRNAs, and mitochondria involved in this type of cell death.