Pericardial Thickness Measured With Transesophageal Echocardiography: Feasibility and Potential Clinical Usefulness

AbstractObjectives. This study assessed the reliability of transesophageal echocardiographic measurements of pericardial thickness and the potential diagnostic usefulness of this technique.Background. Transthoracic echocardiography cannot reliably detect thickened pericardium. The superior resolution achieved with transesophageal echocardiography should allow better pericardial definition.Methods. Pericardial thickness measured at 26 locations in 11 patients with constrictive pericarditis who underwent intraoperative transesophageal echocardiography was compared with pericardial thickness measured with electron beam computed tomography. Intraobserver and interobserver variabilities were determined. Pericardial thickness was then measured in 21 normal subjects. With these values as a guide, two observers reviewed 37 transesophageal echocardiographic studies to determine whether echocardiographic measurement of pericardial thickness could be used to distinguish diseased from normal pericardium.Results. The correlation between echocardiographic and computed tomographic measurements (r ≥ 0.95, SE ≤ 0.06 mm, p < 0.0001) was excellent. The ±2 SD limits of agreement were ±1.0 mm or less for pericardial thickness <5.5 mm and ±2.0 mm or less for the entire range of thicknesses. Intraobserver and interobserver agreements were good. Mean normal pericardial thickness was 1.2 ± 0.8 mm (±2 SD) and did not exceed 2.5 mm. Pericardial thickness ≥3 mm on transesophageal echocardiography was 95% sensitive and 86% specific for the detection of thickened pericardium.Conclusions. Measurement of pericardial thickness with transesophageal echocardiography is reproducible and should be a valuable adjunct in assessing constrictive pericarditis.(J Am Coll Cardiol 1997;29:1317–23

Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting

Sex, gender, and health biotechnology: points to consider

<p>Abstract</p> <p>Background</p> <p>Reproductive technologies have been extensively debated in the literature. As well, feminist economists, environmentalists, and agriculturalists have generated substantial debate and literature on gender. However, the implications for women of health biotechnologies have received relatively less attention. Surprisingly, while gender based frameworks have been proposed in the context of public health policy, practice, health research, and epidemiological research, we could identify no systematic framework for gender analysis of health biotechnology in the developing world.</p> <p>Discussion</p> <p>We propose sex and gender considerations at five critical stages of health biotechnology research and development: priority setting; technology design; clinical trials; commercialization, and health services delivery.</p> <p>Summary</p> <p>Applying a systematic sex and gender framework to five key process stages of health biotechnology research and development could be a first step towards unlocking the opportunities of this promising science for women in the developing world.</p

Predictive value of S100-B and copeptin for outcomes following seizure: the BISTRO International Cohort Study.

OBJECTIVE: To evaluate the performance of S100-B protein and copeptin, in addition to clinical variables, in predicting outcomes of patients attending the emergency department (ED) following a seizure. METHODS: We prospectively included adult patients presented with an acute seizure, in four EDs in France and the United Kingdom. Participants were followed up for 28 days. The primary endpoint was a composite of seizure recurrence, all-cause mortality, hospitalization or rehospitalisation, or return visit in the ED within seven days. RESULTS: Among the 389 participants included in the analysis, 156 (40%) experienced the primary endpoint within seven days and 195 (54%) at 28 days. Mean levels of both S100-B (0.11 μg/l [95% CI 0.07-0.20] vs 0.09 μg/l [0.07-0.14]) and copeptin (23 pmol/l [9-104] vs 17 pmol/l [8-43]) were higher in participants meeting the primary endpoint. However, both biomarkers were poorly predictive of the primary outcome with a respective area under the receiving operator characteristic curve of 0.57 [0.51-0.64] and 0.59 [0.54-0.64]. Multivariable logistic regression analysis identified higher age (odds ratio [OR] 1.3 per decade [1.1-1.5]), provoked seizure (OR 4.93 [2.5-9.8]), complex partial seizure (OR 4.09 [1.8-9.1]) and first seizure (OR 1.83 [1.1-3.0]) as independent predictors of the primary outcome. A second regression analysis including the biomarkers showed no additional predictive benefit (S100-B OR 3.89 [0.80-18.9] copeptin OR 1 [1.00-1.00]). CONCLUSION: The plasma biomarkers S100-B and copeptin did not improve prediction of poor outcome following seizure. Higher age, a first seizure, a provoked seizure and a partial complex seizure are independently associated with adverse outcomes

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Shared genetic risk between eating disorder- and substance-use-related phenotypes:Evidence from genome-wide association studies

First published: 16 February 202