Impact of Chlamydia trachomatis in the reproductive setting: British Fertility Society Guidelines for practice

Chlamydia trachomatis infection of the genital tract is the most common sexually transmitted infection and has a world-wide distribution. The consequences of infection have an adverse effect on the reproductive health of women and are a common cause of infertility. Recent evidence also suggests an adverse effect on male reproduction. There is a need to standardise the approach in managing the impact of C. trachomatis infection on reproductive health. We have surveyed current UK practice towards screening and management of Chlamydia infections in the fertility setting. We found that at least 90% of clinicians surveyed offered screening. The literature on this topic was examined and revealed a paucity of solid evidence for estimating the risks of long-term reproductive sequelae following lower genital tract infection with C. trachomatis. The mechanism for the damage that occurs after Chlamydial infections is uncertain. However, instrumentation of the uterus in women with C. trachomatis infection is associated with a high risk of pelvic inflammatory disease, which can be prevented by appropriate antibiotic treatment and may prevent infected women from being at increased risk of the adverse sequelae, such as ectopic pregnancy and tubal factor infertility. Recommendations for practice have been proposed and the need for further studies is identified

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Multifrequency variability of the blazar AO 0235+164 the WEBT campaign in 2004-2005 and long-term SED analysis

A huge multiwavelength campaign targeting the blazar AO 0235+164 was organized by the Whole Earth Blazar Telescope (WEBT) in 2003-2005 to study the variability properties of the source. Monitoring observations were carried out at cm and mm wavelengths, and in the near-IR and optical bands, while three pointings by the XMM-Newton satellite provided information on the X-ray and UV emission. We present the data acquired during the second observing season, 2004-2005, by 27 radio-to-optical telescopes. They reveal an increased near-IR and optical activity with respect to the previous season. Increased variability is also found at the higher radio frequencies, down to 15 GHz, but not at the lower ones. The radio (and optical) outburst predicted to peak around February-March 2004 on the basis of the previously observed 5-6 yr quasi-periodicity did not occur. The analysis of the optical light curves reveals now a longer characteristic time scale of 8 yr, which is also present in the radio data. The spectral energy distributions corresponding to the XMM-Newton observations performed during the WEBT campaign are compared with those pertaining to previous pointings of X-ray satellites. Bright, soft X-ray spectra can be described in terms of an extra component, which appears also when the source is faint through a hard UV spectrum and a curvature of the X-ray spectrum. Finally, there might be a correlation between the X-ray and optical bright states with a long time delay of about 5 yr, which would require a geometrical interpretation

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease