Cellular circadian period length inversely correlates with HbA1c levels in individuals with type 2 diabetes.

AIMS/HYPOTHESIS: The circadian system plays an essential role in regulating the timing of human metabolism. Indeed, circadian misalignment is strongly associated with high rates of metabolic disorders. The properties of the circadian oscillator can be measured in cells cultured in vitro and these cellular rhythms are highly informative of the physiological circadian rhythm in vivo. We aimed to discover whether molecular properties of the circadian oscillator are altered as a result of type 2 diabetes. METHODS: We assessed molecular clock properties in dermal fibroblasts established from skin biopsies taken from nine obese and eight non-obese individuals with type 2 diabetes and 11 non-diabetic control individuals. Following in vitro synchronisation, primary fibroblast cultures were subjected to continuous assessment of circadian bioluminescence profiles based on lentiviral luciferase reporters. RESULTS: We observed a significant inverse correlation (ρ = -0.592; p < 0.05) between HbA1c values and circadian period length within cells from the type 2 diabetes group. RNA sequencing analysis conducted on samples from this group revealed that ICAM1, encoding the endothelial adhesion protein, was differentially expressed in fibroblasts from individuals with poorly controlled vs well-controlled type 2 diabetes and its levels correlated with cellular period length. Consistent with this circadian link, the ICAM1 gene also displayed rhythmic binding of the circadian locomotor output cycles kaput (CLOCK) protein that correlated with gene expression. CONCLUSIONS/INTERPRETATION: We provide for the first time a potential molecular link between glycaemic control in individuals with type 2 diabetes and circadian clock machinery. This paves the way for further mechanistic understanding of circadian oscillator changes upon type 2 diabetes development in humans. DATA AVAILABILITY: RNA sequencing data and clinical phenotypic data have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the European Bioinformatics Institute (EBI) and the Centre for Genomic Regulation (CRG), ega-box-1210, under accession no. EGAS00001003622.

Low risk of electromagnetic interference between smartphones and contemporary implantable cardioverter defibrillators.

AIMS: Manufacturers of implantable cardioverter defibrillators (ICDs) recommend that cell phones be maintained at a distance of ∼15 cm from the implanted device in order to avoid risk of dysfunction due to electromagnetic interference (EMI). Data relating to this issue are outdated and do not reflect modern technology. Our aim was to evaluate whether EMI is still an issue with contemporary ICDs and smartphones. METHODS AND RESULTS: Consecutive patients implanted with a wireless-enabled ICD were tested for potential interference with two models of recent 4G smartphones in conditions intended to maximize risk of EMI. A magnet effect (due to the phone speakers) was tested by placing the smartphones in the standby mode directly over the ICD generator. The presence of EMI artefacts on the real-time electrograms was evaluated by placing the smartphones in the standby, dialling, and operating modes directly over the generator casing and over the parasternal region in the vicinity of the ventricular lead. A total of 63 patients equipped with 29 different models of single, dual, or biventricular ICDs from five major manufacturers were included. None of the patients showed any evidence of interference with the smartphones during any of the 882 tests. CONCLUSION: The risk of EMI between modern smartphones and contemporary ICDs is low. This is probably due to the filters incorporated in the ICDs and low emission by the phones, as well as the small size of the magnets in the smartphones tested. STUDY REGISTRATION: NCT02330900 (http://www.clinicaltrials.gov).

Severity of pain is associated with insufficient energy coverage in hospitalised patients: A cross-sectional study.

BACKGROUND & AIMS: The severity of pain is routinely assessed in hospitalised patients but the impact of pain and pain control on energy coverage has been poorly studied. This One-day cross-sectional observational study assessed the association between severity of pain and coverage of energy needs in hospitalised patients. METHODS: Foods provided and consumed were assessed on one day by dedicated dieticians for unselected hospitalised patients receiving three meals per day. Severity of pain was evaluated by a visual analogue scale at the mealtimes, averaged over the study day, and categorized as no pain, slight, moderate or severe pain. The coverage of energy needs was expressed in percentage of predicted needs. RESULTS: Among the 755 included patients, 63% reported having pain. Severe pain was associated with a lower energy coverage than no pain (p = 0.001) or slight pain (p = 0.001). Insufficient energy coverage, defined as ≤70% of predicted needs, occurred in 13% of the patients. In univariate logistic regressions, predictors of insufficient energy coverage were severe pain as compared to no pain (OR 2.38; 95% CI 1.21, 4.64) and treatment with opioid drugs as compared to no pain killer (OR 1.73; 95% CI 1.07, 2.79). When including sex, age, body mass index, treatment with analgesics and severity of pain in a multivariate logistic regression, severe pain more than doubled the risk of insufficient energy coverage (OR 2.32; CI 1.15, 4.66). CONCLUSIONS: Patients experiencing severe pain have a high risk of insufficient energy coverage. Optimal pain control is probably critical to prevent underfeeding in the hospital. TRIAL REGISTRATION: Identifier no NCT02463565 on www.ClinicalTrials.gov.

Safety of Bioelectrical Impedance Analysis in Patients Equipped With Implantable Cardioverter Defibrillators.

BACKGROUND: Current guidelines warn of potential electromagnetic interferences (EMI) when using bioelectrical impedance analysis (BIA) to measure body composition in patients equipped with implantable cardioverter-defibrillators (ICDs). We aimed to test the occurrence of EMI in a setting where this risk was experimentally maximized. MATERIALS AND METHODS: Outpatients scheduled for routine ICD controls simultaneously underwent a BIA measurement using an electrical current of 0.8 mAmp at frequencies from 5-100 kHz. ICD sensitivity levels were set to maximum levels while therapies were temporarily inactivated. The device electrograms were monitored in real time to detect sensed and/or visible EMI during BIA measurement. RESULTS: A total of 63 patients equipped with single-chamber (n = 13), dual-chamber (n = 18), or biventricular (n = 32) ICDs from 5 major manufacturers were included. No EMI were detected by the ICDs in these patients, nor were any artifacts visualized during real-time electrogram recordings. CONCLUSION: BIA can be safely performed in patients equipped with ICDs without cardiac monitoring. Current guidelines should be updated accordingly.

Paraoxonase 1 (PON1) and pomegranate influence circadian gene expression and period length.

The circadian timing system regulates key aspects of mammalian physiology. Here, we analyzed the effect of the endogenous antioxidant paraoxonase 1 (PON1), a high-density lipoprotein-associated lipolactonase that hydrolyses lipid peroxides and attenuates atherogenesis, on circadian gene expression in C57BL/6J and PON1KO mice fed a normal chow diet or a high-fat diet (HFD). Expression levels of core-clock transcripts Nr1d1, Per2, Cry2 and Bmal1 were altered in skeletal muscle in PON1-deficient mice in response to HFD. These findings were supported by circadian bioluminescence reporter assessments in mouse C2C12 and human primary myotubes, synchronized in vitro, where administration of PON1 or pomegranate juice modulated circadian period length.

Identification of CHEK1, SLC26A4, c-KIT, TPO and TG as new biomarkers for human follicular thyroid carcinoma.

The search for preoperative biomarkers for thyroid malignancies, in particular for follicular thyroid carcinoma (FTC) diagnostics, is of utmost clinical importance. We thus aimed at screening for potential biomarker candidates for FTC. To evaluate dynamic alterations in molecular patterns as a function of thyroid malignancy progression, a comparative analysis was conducted in clinically distinct subgroups of FTC and poorly differentiated thyroid carcinoma (PDTC) nodules. NanoString analysis of FFPE samples was performed in 22 follicular adenomas, 56 FTC and 25 PDTC nodules, including oncocytic and non-oncocytic subgroups. The expression levels of CHEK1, c-KIT, SLC26A4, TG and TPO were significantly altered in all types of thyroid carcinomas. Based on collective changes of these biomarkers which correlating among each other, a predictive score has been established, allowing for discrimination between benign and FTC samples with high sensitivity and specificity. Additional transcripts related to thyroid function, cell cycle, circadian clock, and apoptosis regulation were altered in the more aggressive oncocytic subgroups only, with expression levels correlating with disease progression. Distinct molecular patterns were observed for oncocytic and non-oncocytic FTCs and PDTCs. A predictive score correlation coefficient based on collective alterations of identified here biomarkers might help to improve the preoperative diagnosis of FTC nodules.

Impact of body composition changes on risk of all-cause mortality in older adults.

PURPOSE: This study evaluates the relationship between body mass index (BMI), fat mass index (FMI) and fat-free mass index (FFMI) changes and mortality in persons ≥65 years. METHODS: Adults ≥65 years with at least two body composition measurements (BCM) between 1990 and 2011 were included. We excluded persons who died within one month of the second BCM and who had two single BCM in a one-month timeframe. Mortality data was retrieved until December 2012. For each person, we calculated the regression slopes for BMI, FMI and FFMI changes. Significant positive slopes were categorized as "gain", negative slopes as "loss" and the others as "maintenance". The impact of body composition changes was evaluated by Cox regression models while adjusting for sex, age, co-morbidities and body composition at the last measurement. RESULTS: We included 791 persons with 3049 BCM. After adjustment for sex, and age and co-morbidities, a loss of FFMI, but not of FMI or BMI, increased the risk of mortality (HR 2.02, 95%CI 1.28-3.19). The prediction of mortality with FFMI loss remained significant when further adjusting for FMI loss and the last available body composition (HR 1.68, 95%CI 1.04-2.70). CONCLUSIONS: FFMI loss is related to increased mortality in older persons.

Fat-free mass at admission predicts 28-day mortality in intensive care unit patients: the international prospective observational study Phase Angle Project.

PURPOSE: Phase angle as measured by bioelectrical impedance analysis reflects fat-free mass. Fat-free mass loss relates to worse prognosis in chronic diseases. Primary aim of this study was: to determine the association between fat-free mass at intensive care unit admission and 28-day mortality. METHODS: Ten centres in nine countries participated in this multicentre prospective observational study. The inclusion criteria were age >18 years; expected length of stay >48 h; absence of pacemaker, heart defibrillator implant, pregnancy and lactation. Fat-free mass was assessed by measurement of the 50-kHz phase angle at admission. The primary endpoint was 28-day mortality. The area under the receiver operating characteristic curve (AUC) was used to assess prediction of 28-day mortality by fat-free mass at ICU admission. The variables associated with 28-day mortality were analysed by means of multivariable logistic regression. RESULTS: Of the 3605 patients screened, 931 were analysed: age 61 ± 16 years, male 60 %, APACHE II 19 ± 9, body mass index 26 ± 6, day 1 phase angle 4.5° ± 1.9°. Day 1 phase angle was lower in patients who eventually died than in survivors (4.1° ± 2.0° vs. 4.6° ± 1.8°, P = 0.001). The day 1 phase angle AUC for 28-day mortality was 0.63 [0.58-0.67]. In multivariable analysis, the following were independently associated with 28-day mortality: age (adjusted odds ratio (aOR) 1.014 [95 % confidence interval 1.002-1.027], P = 0.03), day 1 phase angle (aOR 0.86 [0.78-0.96], P = 0.008), APACHE II (aOR 1.08 [1.06-1.11], P < 0.001), surgical patient (aOR 0.51 [0.33-0.79], P = 0.002), and admission for other diagnosis (aOR 0.39 [0.21-0.72], P = 0.003). A multivariable combined score improved the predictability of 28-day mortality: AUC = 0.79 [0.75-0.82]. CONCLUSION: Low fat-free mass at ICU admission is associated with 28-day mortality. A combined score improves mortality predictability. TRIAL REGISTRATION: NCT01907347 ( http://www.clinicaltrials.gov ).

Body composition and all-cause mortality in subjects older than 65 y.

BACKGROUND: A low or high body mass index (BMI) has been associated with increased mortality risk in older subjects without taking fat mass index (FMI) and fat-free mass index (FFMI) into account. This information is essential because FMI is modulated through different healthcare strategies than is FFMI. OBJECTIVE: We aimed to determine the relation between body composition and mortality in older subjects. DESIGN: We included all adults ≥65 y old who were living in Switzerland and had a body-composition measurement by bioelectrical impedance analysis at the Geneva University Hospitals between 1990 and 2011. FMI and FFMI were divided into sex-specific quartiles. Quartile 1 (i.e., the reference category) corresponded to the lowest FMI or FFMI quartile. Mortality data were retrieved from the hospital database, the Geneva death register, and the Swiss National Cohort until December 2012. Comorbidities were assessed by using the Cumulative Illness Rating Scale. RESULTS: Of 3181 subjects included, 766 women and 1007 men died at a mean age of 82.8 and 78.5 y, respectively. Sex-specific Cox regression models, which were used to adjust for age, BMI, smoking, ambulatory or hospitalized state, and calendar time, showed that body composition did not predict mortality in women irrespective of whether comorbidities were taken into account. In men, risk of mortality was lower with FFMI in quartiles 3 and 4 [HR: 0.78 (95% CI: 0.62, 0.98) and 0.64 (95% CI: 0.49, 0.85), respectively] but was not affected by FMI. When comorbidities were adjusted for, FFMI in quartile 4 (>19.5 kg/m(2)) still predicted a lower risk of mortality (HR: 0.72; 95% CI: 0.54, 0.96). CONCLUSIONS: Low FFMI is a stronger predictor of mortality than is BMI in older men but not older women. FMI had no impact on mortality. These results suggest potential benefits of preventive interventions with the aim of maintaining muscle mass in older men. This trial was registered at clinicaltrials.gov as NCT01472679.

Identification of new biomarkers for human papillary thyroid carcinoma employing NanoString analysis.

We previously reported an upregulation of the clock transcript BMAL1, correlating with TIMP1 expression in fresh-frozen samples from papillary thyroid carcinoma (PTC). Since frozen postoperative biopsy samples are difficult to obtain, we aimed to validate the application of high-precision NanoString analysis for formalin-fixed paraffin-embedded (FFPE) thyroid nodule samples and to screen for potential biomarkers associated with PTC. No significant differences were detected between fresh-frozen and FFPE samples. NanoString analysis of 51 transcripts in 17 PTC and 17 benign nodule samples obtained from different donors and in 24 pairs of benign and PTC nodules, obtained from the same donor (multinodular goiters), confirmed significant alterations in the levels of BMAL1, c-MET, c-KIT, TIMP1, and other transcripts. Moreover, we identified for the first time alterations in CHEK1 and BCL2 levels in PTC. A predictive score was established for each sample, based on the combined expression levels of BMAL1, CHEK1, c-MET, c-KIT and TIMP1. In combination with BRAF mutation analysis, this predictive score closely correlated with the clinicopathological characteristics of the analyzed thyroid nodules. Our study identified new thyroid transcripts with altered levels in PTC using the NanoString approach. A predictive score correlation coefficient might contribute to improve the preoperative diagnosis of thyroid nodules.

Healthcare-associated infections are associated with insufficient dietary intake: an observational cross-sectional study.

BACKGROUND: Indicators to predict healthcare-associated infections (HCAI) are scarce. Malnutrition is known to be associated with adverse outcomes in healthcare but its identification is time-consuming and rarely done in daily practice. This cross-sectional study assessed the association between dietary intake, nutritional risk, and the prevalence of HCAI, in a general hospital population. METHODS AND FINDINGS: Dietary intake was assessed by dedicated dieticians on one day for all hospitalized patients receiving three meals per day. Nutritional risk was assessed using Nutritional Risk Screening (NRS)-2002, and defined as a NRS score ≥ 3. Energy needs were calculated using 110% of Harris-Benedict formula. HCAIs were diagnosed based on the Center for Disease Control criteria and their association with nutritional risk and measured energy intake was done using a multivariate logistic regression analysis. From 1689 hospitalised patients, 1024 and 1091 were eligible for the measurement of energy intake and nutritional risk, respectively. The prevalence of HCAI was 6.8%, and 30.1% of patients were at nutritional risk. Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002). The proportion of patients at nutritional risk was not significantly different between patients with and without HCAI (35.6% vs.29.7%, P = 0.28), respectively. Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis. CONCLUSION: Measured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients. This suggests that insufficient dietary intake could be a risk factor of HCAI, without excluding reverse causality. Randomized trials are needed to assess whether improving energy intake in patients identified with decreased dietary intake could be a novel strategy for HCAI prevention.