Suppression of alcohol-induced hypertension by dexamethasone

BACKGROUND. Alcohol consumption is associated with an increased incidence of hypertension and stroke, but the triggering mechanisms are unclear. In animals, alcohol causes activation of the sympathetic nervous system and also stimulates the release of corticotropin-releasing hormone (CRH), which has sympatho-excitatory effects when administered centrally. METHODS. To determine whether alcohol evokes sympathetic activation and whether such activation is attenuated by the inhibition of CRH release, we measured blood pressure, heart rate, and sympathetic-nerve action potentials (using intraneural microelectrodes) in nine normal subjects before and during an intravenous infusion of alcohol (0.5 g per kilogram of body weight over a period of 45 minutes) and for 75 minutes after the infusion. Each subject received two infusions, one after the administration of dexamethasone (2 mg per day) and one after the administration of a placebo for 48 hours. RESULTS. The infusion of alcohol alone evoked a marked (P < 0.001) and progressive increase in the mean (+/- SD) rate of sympathetic discharge, from 16 +/- 3 bursts per minute at base line to 30 +/- 8 bursts per minute at the end of the two-hour period. This sympathetic activation was accompanied during the second hour by an increase in mean arterial pressure of 10 +/- 5 mm Hg (P < 0.001). After the administration of dexamethasone, the alcohol infusion had no detectable sympathetic effect. The dexamethasone-induced suppression of sympathetic activation was associated with a decrease in mean arterial pressure of 7 +/- 6 mm Hg (P < 0.001) during the alcohol infusion and with suppression of the pressor effect during the second hour. CONCLUSIONS. Alcohol induces pressor effects by sympathetic activation that appear to be centrally mediated. It is possible that these alcohol-induced hemodynamic and sympathetic actions could participate in triggering cardiovascular events

The Benefit of Menopausal Hormone Therapy on Bone Density and Microarchitecture Persists After its Withdrawal.

Menopausal hormone therapy (MHT) favorably affects bone mineral density (BMD). Whether MHT also affects bone microarchitecture, as assessed by trabecular bone score (TBS), has never been evaluated. Our objective was to assess the effect of MHT on TBS and BMD before and after its withdrawal. This was a cross-sectional study. This study included the general community. Data were collected from the OsteoLaus cohort (1500 women aged 50-80 years). After exclusion of women with bone-modulating treatments, 1279 women were categorized according to MHT status into current (CU), past (PU), and never (NU) users. Spine TBS and BMD at lumbar spine, femoral neck, and total hip were assessed by dual X-ray absorptiometry. Age- and body mass index-adjusted analysis showed higher TBS values in CU vs PU or NU (1.31 ± 0.01, 1.29 ± 0.01, and 1.27 ± 0.01, respectively; P < .001). All BMD values were significantly higher in CU vs PU or NU. Compared to NU, PU exhibited higher lumbar spine (0.94 ± 0.01 vs 0.91 ± 0.01 g/cm(2); P = .017) and total hip (0.86 ± 0.01 vs 0.84 ± 0.01 g/cm(2); P = .026) BMD and a trend for higher TBS (P = .066). The 10-year loss of TBS and BMD at lumbar spine and total hip was significantly lower for both CU and PU vs NU. MHT duration had no effect on bone parameters. In PU, the residual effect on TBS and BMD was significantly more prominent in early discontinuers (<2 years). MHT is associated with bone microarchitecture preservation, as assessed by TBS. The effect of MHT on TBS and BMD persists at least 2 years after withdrawal

The Metabolic Benefits of Menopausal Hormone Therapy Are Not Mediated by Improved Nutritional Habits. The OsteoLaus Cohort.

Menopause alters body composition by increasing fat mass. Menopausal hormone therapy (MHT) is associated with decreased total and visceral adiposity. It is unclear whether MHT favorably affects energy intake. We aimed to assess in the OsteoLaus cohort whether total energy intake (TEI) and/or diet quality (macro- and micronutrients, dietary patterns, dietary scores, dietary recommendations)-evaluated by a validated food frequency questionnaire-differ in 839 postmenopausal women classified as current, past or never MHT users. There was no difference between groups regarding TEI or consumption of macronutrients. After multivariable adjustment, MHT users were less likely to adhere to the unhealthy pattern 'fat and sugar: Current vs. never users [OR (95% CI): 0.48 (0.28-0.82)]; past vs. never users [OR (95% CI): 0.47 (0.27-0.78)]. Past users exhibited a better performance in the revised score for Mediterranean diet than never users (5.00 ± 0.12 vs. 4.63 ± 0.08, p < 0.04). Differences regarding compliance with dietary recommendations were no longer significant after adjustment for covariates. Overall, these results argue against a major role of TEI and diet quality as possible mediators of the MHT metabolic benefits. Future research on this relationship should focus on other potential targets of MHT, such as resting energy expenditure and physical activity

Towards mapping neuro-behavioral heterogeneity of psychedelic neurobiology in humans

Precision psychiatry aims to identify markers of inter-individual variability that allow predicting the right treatment for each patient. However, bridging the gap between molecular-level manipulations and neural systems-level functional alterations remains an unsolved problem in psychiatry. After decades of low success rates in pharmaceutical R&D for psychiatric drugs, multiple studies now point to the potential of psychedelics as a promising fast-acting and long-lasting treatment for some psychiatric symptoms. Yet, given the highly psychoactive nature of these substances, a precision medicine approach is essential to map the neural signals related to clinical efficacy in order to identify patients who can maximally benefit from this treatment. Recent studies have shown that bridging the gap between pharmacology, systems-level neural response in humans and individual experience is possible for psychedelic substances, therefore paving the way for a precision neuropsychiatric therapeutic development. Specifically, it has been shown that the integration of brain-wide PET or transcriptomic data, i.e. receptor distribution for the serotonin 2A receptor, with computational neuroimaging methods can simulate the effect of psychedelics on the human brain. These novel 'computational psychiatry' approaches allow for modeling inter-individual differences in neural as well as subjective effects of psychedelic substances. Collectively, this review provides a deep dive into psychedelic pharmaco-neuroimaging studies with a core focus on how recent computational psychiatry advances in biophysically based circuit modeling can be leveraged to predict individual responses. Finally, we emphasize the importance of human pharmacological neuroimaging for the continued precision therapeutic development of psychedelics. Keywords: computational modeling; fMRI; neuroimaging; precision psychiatry; psychedelics; serotonin

Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits

Comparison of the European and U.S. guidelines for lipid-lowering therapy in primary prevention of cardiovascular disease.

Population-wide impacts of new guidelines in the primary prevention of atherosclerotic cardiovascular disease (ASCVD) should be explored in independent cohorts. Assess and compare the lipid-lowering therapy eligibility and predictive classification performance of 2016 and 2021 European Society of Cardiology (ESC), 2019 American Heart Association/American College of Cardiology (AHA/ACC) and 2022U.S. Preventive Services Task Force (USPSTF) guidelines. Participants from the Colaus|PsyCoLaus study, without ASCVD and not taking lipid-lowering therapy at baseline. Derivation of 10-year risk for ASCVD using SCORE1, SCORE2 (including SCORE2-OP) and PCE. Computation of the number of people eligible for lipid-lowering therapy based on each guideline and assessment of discrimination and calibration metrics of the risk models using first incident ASCVD as an outcome. Among 4,092 individuals, 158 (3.9%) experienced an incident ASCVD during a median follow-up of 9 years (IQR, 1.1). Lipid-lowering therapy was recommended or considered in 40.2% (95% CI, 38.2-42.2), 26.4% (24.6-28.2), 28.6% (26.7-30.5) and 22.6% (20.9-24.4) of women and in 62.1% (59.8-64.3), 58.7% (56.4-61.0), 52.6% (50.3-54.9) and 48.4% (46.1-50.7) of men according to 2016 ESC, 2021 ESC, 2019 AHA/ACC and 2022 USPSTF guidelines, respectively. 43.3% and 46.7% of women facing an incident ASCVD were not eligible for lipid-lowering therapy at baseline according to 2021 ESC and 2022 USPSTF, compared to 21.7% and 38.3% using 2016 ESC and 2019 AHA/ACC, respectively. Both 2022 USPSTF and 2021 ESC guidelines particularly reduced lipid-lowering therapy eligibility in women. Nearly half of women who faced an incident ASCVD were not eligible for lipid-lowering therapy

Evidence for tuning adipocytes ICER levels for obesity care.

Abnormal adipokine production, along with defective uptake and metabolism of glucose within adipocytes, contributes to insulin resistance and altered glucose homeostasis. Recent research has highlighted one of the mechanisms that accounts for impaired production of adiponectin (ADIPOQ) and adipocyte glucose uptake in obesity. In adipocytes of human obese subjects and mice fed with a high fat diet, the level of the inducible cAMP early repressor (ICER) is diminished. Reduction of ICER elevates the cAMP response element binding protein (CREB) activity, which in turn increases the repressor activating transcription factor 3. In fine, the cascade triggers reduction in the ADIPOQ and GLUT4 levels, which ultimately hampers insulin-mediated glucose uptake. The c-Jun N-terminal kinase (JNK) interacting-protein 1, also called islet brain 1 (IB1), is a target of CREB/ICER that promotes JNK-mediated insulin resistance in adipocytes. A rise in IB1 and c-Jun levels accompanies the drop of ICER in white adipose tissues of obese mice when compared with mice fed with a chow diet. Other than the expression of ADIPOQ and glucose transport, decline in ICER expression might impact insulin signaling. Impairment of ICER is a critical issue that will need major consideration in future therapeutic purposes

Social inequalities in sleep-disordered breathing: Evidence from the CoLaus|HypnoLaus study.

Sleep-disordered breathing is a common condition, related to a higher cardiometabolic and neurocognitive risk. The main risk factors for sleep-disordered breathing include obesity, craniofacial characteristics, male sex and age. However, some studies have suggested that adverse socioeconomic circumstances and lifestyle-related behaviours such as smoking and alcohol use, may also be risk factors for sleep-disordered breathing. Here, we investigate the associations between socioeconomic status and sleep-disordered breathing, as measured by sleep apnea-hypopnea and oxygen desaturation indexes. Furthermore, we assess whether these associations are explained by lifestyle-related factors (smoking, sedentary behaviour, alcohol use and body mass index [BMI]). We used data from the CoLaus|HypnoLaus study, a population-based study including 2162 participants from Lausanne (Switzerland). Socioeconomic status was measured through occupation and education. Sleep-disordered breathing was assessed through polysomnography and measured using the apnea-hypopnea index (AHI: number of apnea/hypopnea events/hr: ≥15/≥30 events), and the ≥3% oxygen desaturation index (ODI: number of oxygen desaturation events/hr: ≥15/≥30 events). Lower occupation and education were associated with higher AHI and ODI (occupation: AHI30, odds ratio (OR) = 1.88, 95% confidence interval (CI) [1.07; 3.31]; ODI30, OR = 2.29, 95% CI [1.19; 4.39]; education: AHI30, OR = 1.21, 95% CI [0.85; 1.72]; ODI30, OR = 1.26, 95% CI [0.83; 1.91]). BMI was associated with socioeconomic status and AHI/ODI, and contributed to the socioeconomic gradient in SDB, with mediation estimates ranging between 43% and 78%. In this Swiss population-based study, we found that low socioeconomic status is a risk factor for sleep-disordered breathing, and that these associations are partly explained by BMI. These findings provide a better understanding of the mechanisms underlying social differences in sleep-disordered breathing and may help implement policies for identifying high-risk profiles for this disorder

Objective Sleep Structure and Cardiovascular Risk Factors in the General Population: The HypnoLaus Study.

STUDY OBJECTIVES: To evaluate the association between objective sleep measures and metabolic syndrome (MS), hypertension, diabetes, and obesity. DESIGN: Cross-sectional study. SETTING: General population sample. PARTICIPANTS: There were 2,162 patients (51.2% women, mean age 58.4 ± 11.1). INTERVENTIONS: Patients were evaluated for hypertension, diabetes, overweight/obesity, and MS, and underwent a full polysomnography (PSG). MEASUREMENTS AND RESULTS: PSG measured variables included: total sleep time (TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index (ArI). In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, and sleep efficiency, and increased ArI. After adjustment for age, sex, smoking, alcohol, physical activity, drugs that affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in patients without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes, and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. CONCLUSIONS: In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes, and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders

A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature

$\textbf{BACKGROUND}$ Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. $\textbf{METHODS AND FINDINGS}$ We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. $\textbf{CONCLUSIONS}$ This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.This study was supported by the Medical Research Council UK (grant reference no. MC_UU_12015/1), http://gtr.rcuk.ac.uk/projects?ref=MC_UU_12015/1; Netherlands Organization for Scientific Research (NWO project number 825.13.004), http://www.nwo.nl/en/research-and-results/research-projects/i/85/10585.html; Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement no. 115372, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013), http://www.emif.eu/about. GSK provided support in the form of salaries for DW, DJN, AS. Pfizer provided support in the form of salary to JMB